The author dedicated the work to the public domain by waiving all of his or her rights to the work worldwide under copyright law and all related or neighboring legal rights he or she had in the work, to the extent allowable by law.

After the publication of the original publication, several minor errors were discovered.
Most errors were found in the statistical tables. This bulletin summarizes the results of a multi-
year cooperative investigation on spring and groundwater quality between the Florida
Department of Environmental Protection's FGS and the Bureau of Watershed Management,
Division of Environmental Assessment and Restoration. The data presented will be useful to
scientists, planners, and citizens in understanding the quality of Florida's groundwater resources.

Over the past several decades, it has been observed that the flows in Florida's springs are
declining and water quality is degrading. The primary chemical concern is considered to be
increased nutrients, including soluble forms of nitrogen and phosphorus. The sources are
predominantly from animal waste, human waste, and from the synthetic fertilizers used on lawns,
golf courses, or for agricultural activities.

In recognition of these issues, the Secretary of the Florida Department of Environmental
Protection (FDEP) directed the formation of the Florida Springs Task Force in 1999. The multi-
agency task force consisted of 16 scientists, planners, and citizens who were concerned about the
"environmental health" of Florida's springs. By 2000 the task force made a series of
recommendations to protect and restore Florida's springs. They are outlined in detail in Florida's
Springs: Strategies for Protection and Restoration (Florida Springs Task Force, 2000). Two of
the recommendations were to:

(1) Implement springs monitoring programs to detect and document long-term
trends in water quantity and quality

(2) Conduct research that will allow cause-and-effect relationships to be
established between land use and water management activities.

The purpose of monitoring is to both support research efforts and to confirm the effectiveness of
spring protection efforts. As a direct result of the first recommendation, the Florida Geological
Survey (FGS) took the lead in implementing a spring monitoring program. By 2004 it published
the latest Springs of Florida bulletin-a descriptive overview of Florida's springs.

The main purposes of this document are to: (1) determine trends in groundwater where
sufficient data are available; (2) establish prototype methods for evaluating and reporting trends
for future applications; and (3) enhance the efforts of determining cause-and-effect relationships
between anthropogenic activities and the resulting spring-water quality and quantity on regional
(water management district-wide) and statewide scales. The reason for the latter is that many
other publications have addressed the causes of trends on an individual spring basis. If we
attempted to develop an exhaustive list of possible causes of trends for each spring, it could take
many years to accomplish. We decided to emphasize regional and statewide scales. An endeavor
of this nature has never been attempted. If regional or statewide trends were found, the causes
and possible solutions to those causes may become the highest priority water management issues.

In order to fully comprehend the implications of trends in springs, a thorough
understanding of the behavior of groundwater in wells is also necessary. In 1983, the FDEP
began a statewide groundwater quality monitoring network (Florida Statutes 403.063). Scott et
al. (1991) stated that the purpose of the network was to detect or predict contamination of
Florida's groundwater resources. Currently, several thousand wells are included in the network.
However, a subset of the wells are conducive to trend analysis (the Temporal Variability

Network, or simply the TV Network). Since the FGS was asked to evaluate data for trends from
springs, it followed to simultaneously do the same for groundwater from TV Network wells.

Approach

The FGS spring monitoring program commenced operations in 2001. For many of the
springs, previous samples had never been collected, so long-term trend analyses were not
possible. However, the FGS contacted each of the four northern water management districts
(WMDs), the U.S. Geological Survey (USGS), and programs within the FDEP to request copies
of their historical spring-water quality and quantity data. The entities each graciously delivered
data to the FGS for analyses. It should be noted that the South Florida Water Management
District (SFWMD) had insufficient data for trend analyses.

The FGS obtained sufficient data, meeting preset criteria, from 58 springs and 46 wells
for the period January 1991 through December 2003. For reference, the study was divided into
three time sequences. Sequence A represents the entire length of the study (1991-2003).
Sequence B represents the January 1, 1991 December 31, 1997 time frame, while Sequence C
represents January 1, 1998 December 31, 2003. The two shorter sequences were used to assist
in identifying and evaluating shorter-term trends. As it turns out, Sequence B coincided with
relatively normal rainfall, whereas Sequence C covered a time that Florida experienced an
extended drought.

The analytes (constituents of interest) for this report can be broken down into five
groups: (1) nutrients, (2) saline (or salt-water), (3) rock-matrix (or rock), (4) field, and (5) other.
Of these, the three major groups are nutrients, saline, and rock-matrix. Nutrients are compounds
that are essential for the growth of living organisms. Unfortunately, high concentrations in
spring-water can adversely affect the biota in spring runs. Saline analytes are related to salts.
The most significant sources of salt are from the ocean or deep groundwater in Florida's
aquifers. High concentrations of saline compounds (e.g. sodium or chloride) can restrict the
usage of water. Rock-matrix analytes have their sources in the aquifer material (e.g. limestones
and dolostones). They occur naturally and, unless they occur in extremely high concentrations,
are generally not harmful to our environment. The field and other analyte groups consist of
miscellaneous constituents that are useful in explaining trends in other analytes.

Think of a trend as a direction of movement (Berube and Boyer, 1985). Although there
are many secondary questions that pertain to trends, trend analysis can be broken down to one
fundamental, primary question, "over time, are conditions changing (getting better or getting
worse), or are they remaining the same?" One can think in terms of concentrations of water
quality (measured by analytes) or water quantity (measured by flow or water levels). Subjective
descriptions-such as better, worse, and remaining the same-are based on objective changes
over time, or trends.

Throughout this report the term significant refers to statistical significance. Some of the
trends reflect very important changes in water quality, whereas some only represent relatively
minor changes in water quality that are not indicative of impending problems. If, during our
analyses, a trend was discovered, it was based on statistical significance. That is, within a

predefined probability, we do not expect the trend to occur randomly. Since not all of the
audience of this report is familiar with the statistical procedures employed, we decided to
simplify the procedures to the extent practical. For this reason, most analyses were restricted to
linear trends, using nonparametric techniques. Data were checked for seasonality, and if found,
were deseasonalized prior to trend analyses using a method recommended by the U.S
Environmental Protection Agency (EPA, 1989). Trend analyses were conducted using the
Mann-Kendall test, while the rates of change over time were determined using the Sen slope
(Gilbert, 1987).

Results and Conclusions

The most important conclusion to be derived from this report is that Florida springs truly
represent the "canary in the coal mine" with respect to assessing regional groundwater quality in
Florida. As will be summarized, springs are apparently much better at indicating over-all change
in a groundwater flow system than wells.

Monitoring wells only allow for the sampling of a discrete portion of the water in an
aquifer. They limit detection to a particular depth interval and a relatively limited spatial extent.
Karstic aquifers are especially limited in this respect as fractures and cavernous conduits may
direct water flow around or below the location of a monitoring well. On the other hand, the
quality of water discharging from a spring is an integral of the water quality of the total flow
system within a springshed. This water is derived from deep and shallow flow systems and
conduit and diffuse flow. Furthermore, the water quality, and flow, data are weighted according
to the relative importance of the flow systems and chemical sources within the springshed. As a
result, springs appear to be much better at detecting regional changes in a springshed water
quality than do wells. This conclusion is supported by the fact that water-quality trends were
much more obvious in spring data than in well data.

Springs

Of the analyte groups, rock-matrix and saline analytes had the greatest frequency of
trends. Both analyte groups showed strong negative correlations with spring flow. For example,
as spring flow decreased saline and rock-matrix analyte concentrations increased. The
relationship was observed throughout the state. The greatest increases in the concentrations of
rock-matrix and saline analytes occurred during a drought that occurred between late 1998 and
mid 2002.

There are several probable explanations and all can be a result of the drought. First,
during the drought there was less rainfall, and consequently there was less surface-water flow.
In karst terrains, much surface-water flows directly to groundwater through sinking streams
(swallets). Typically, this rapidly recharged groundwater is transmitted in well-developed
subsurface conduits. Thus, there is very little contact time with the aquifer matrix before it
discharges from springs, and it tends to have lower concentrations of rock-matrix analytes.
During a drought, there is a decrease in the proportion of freshly recharged "surface water." This,
at least partially explains the correlation between decreased spring discharge and increased
concentrations of rock analytes.

A second probable explanation is related to the removal of older, saline-rich and usually
more mineralized water from storage, often in the deeper portions of the Florida's aquifer
systems. Beneath the state of Florida lies a "lens" of fresh water, which is replenished by
rainfall. Freshly recharged water is flushed through Florida's karstic (sinkholes, caves, springs
etc.) aquifers relatively quickly to springs. In contrast, the deeper water is older (Upchurch,
1992; and Katz, 2004). Because it has been in contact with the aquifer matrix for a relatively
long period of time, the aquifer water has had a longer time to "pick up" dissolved matrix
material constituents such as calcium and magnesium, especially in the Floridan aquifer system.
With longer residence times, the older water tends to have higher concentrations of rock-matrix
material.

A third explanation is similar to the second. Older, mineralized residual saltwater, was
never fully flushed from the rock interstices in some portions of Florida (Johnson and Bush,
1986). With less rainfall during the drought, the water levels in the aquifers were lowered, and
the size of the freshwater "lens" decreased. With decreasing freshwater potentials (e.g., water
levels) the deeper and older connate water can find its way upward toward aquifer discharge
points, such as springs. Thus, during the drought, increased concentrations in rock-matrix and
saline analytes were observed, along with decreases in spring discharges. The trends were
statewide in scale. The magnitude of scale was the most surprising and most significant finding
of the study.

After the driest portion of the drought (2002), Florida's hydrologic conditions began to
recover and the concentrations of both types of analytes began to decrease, as rainfall, recharge,
and spring flow began to increase. The inverse relationship between spring-water discharge, and
both rock-matrix and saline analyte concentrations, was also observed in a study by Katz (2004).
In addition, Katz also found a positive correlation between concentrations of rock and saline
analytes and spring-water age.

Nutrients in groundwater discharging from springs were one of the most important
concerns of the Springs Task Force. Evaluation of trends in this report revealed that nutrient
trends in springs had an uneven, or patchwork, distribution across the state. That is, both
increasing and decreasing nutrient trends were common and were observed throughout Florida.
This suggests that the trends were often related to local land-use and water-use activities. As
such, most nutrient concentrations observed in springs are localized and should be analyzed in
relation to the corresponding springshed.

Nitrogen and phosphorus comprised the most frequent nutrient exhibiting trends.
Nitrogen in the form of nitrate (nitrate plus nitrite as N) had the greatest frequency of increasing
(degrading) trends. However, some springs actually had decreasing nitrate trends. Phosphorus,
as total phosphorus and orthophosphate, had both increasing and decreasing trends, depending on
the springshed.

Note that decreasing nutrient trends are not necessarily good news. During the drought,
an important observation was that some nitrate concentrations had positive correlations with
spring flow. One possible explanation is that nitrogen can be stored in the soils of Florida's
springsheds (Bruland et al., 2008). During the drought, soils may have stored the nitrogen

originating from fertilizer applications and the nitrogen did not find its way to the groundwater
regime. When rainfall conditions return to normal, the soils will release the nitrogen and
concentrations in spring water will eventually increase. On a similar note, decreases in
phosphorus in some areas may likewise not be a reflection of improved management. It is
possible that the upward migration of older water, with different chemistry, reduced the
phosphorus concentrations in many springs. If so, reduction of phosphorus could simply be a by-
product of mixing with deeper, higher pH water-not an improvement in water quality. This
mechanism is discussed by Hem (1985) and by Odum (1953). They indicated that the solubility
of phosphorous can be controlled by pH. Dissolved phosphorous is generally more abundant in
lower pH (more acidic) water. Conversely, higher pH (more basic) water contributes to the
precipitation of phosphate and lowers the concentration of dissolved phosphorous in
groundwater.

Wells

Within Florida's aquifers, the flow paths of spring-water can potentially be from both
deep and shallow sources. Conversely, wells typically are drilled to a specific depth in an
aquifer. Consequently, flow paths of well water are from a much narrower thickness of the
aquifer, relative to spring water flow paths. Although there are exceptions, most of the 46 wells
used in this study generally tap only the shallower portions of the aquifers. The wells tend to be
less than 30 m (100 feet) deep. Because of the shallower depth, the older, deeper, and more
mineralized deeper aquifer water had a lower probability of being observed in the shallow wells.
Thus, rock-matrix and saline trends were not seen as frequently in wells as in springs.
Nevertheless, decreasing trends in water levels within wells were common. In addition, pH-a
field analyte-had a positive correlation with water levels; as water levels in wells decreased, so
did pH.

A possible explanation for this positive correlation is as follows. Well intake zones for
most wells in Florida are generally set at specified depths below the lowest predicted aquifer
water levels. This is done in order to guarantee water to the well during drought conditions.
During dry times the upper surface of the saturated zone is lowered downward toward the
uppermost point of the intake zone. For the aquifers tapped by the 46 shallow wells used in this
study, most recharge is from water, typically rainfall, penetrating the land surface and moving
downward through the soil to the groundwater regime. Rainfall has a lower pH than most
aquifer water. The pH is lowered further as rainwater picks up carbonic acid as it moves
downward through Florida's soils (Freeze and Cherry, 1979; and Upchurch, 1992). Therefore,
as the water table (or the potentiometric surface in confined aquifers) drops, generally the
younger, freshly recharged water with lower pH has an increasing probability of entering well
intake zones. As such, the lowering of the water table is a potential cause for decreasing trends
in pH values across the state during the drought. A detailed description of this hypothesis, along
with other related hypotheses, is discussed in the body of this report.

Another field analyte that displayed a trend was well water temperature. Between 1991
and 2003, its temperature typically increased; the reason is believed to be an increase in air
temperature. Air temperature increased across Florida (Southeast Regional Climate Center,
2006). Since the wells used in this report tend to be shallow, it is believed that well water readily

responded to air temperature changes. On the other hand, the sources of spring water are from
shallow and deep portions of our aquifers. Deeper water tends not to respond to changes in air
temperature. Thus, spring water displayed fewer temperature trends than did well water.

Concerns

Rock-Matrix and Saline Indicators: Saltwater Encroachment

Saltwater encroachment is the displacement of fresh groundwater by the advance of
saltwater due to its greater density (Neuendorf et al., 2005). It can occur during a drought when
recharge declines and the freshwater "lens" shrinks in size. Over geologic time, it can occur with
sea-level rise. It can also occur when excessive groundwater pumping causes the advancement
of saltwater. Freeze and Cherry (1979) use the term saltwater intrusion as the migration of
saltwater into freshwater aquifers under the influence of groundwater development (pumping).
For this paper, we use the term intrusion to indicate a man-induced process and use the term
encroachment to make no distinction between natural and man-made causes.

Figure 1 (top) displays the unconfined, surficial aquifer system. The saltwater/freshwater
interface is represented by a transition zone. During a drought, the water table lowers, the
transition zone migrates inland and the thickness of the freshwater zone ("lens") decreases in
size.

In his work in northeastern Florida, Spechler (2001) mentioned several possible
mechanisms that can drive encroachment and intrusion. During the drought, they included: (1)
the movement of "un-flushed" pockets of relict seawater within the Floridan aquifer system, (2)
the landward movement of the freshwater/saltwater interface, (3) regional upcoming of saltwater
below pumped wells, and (4) the upward leakage of saltwater from deeper, saline water-bearing
zones through confining units. The latter can occur where the units are thin or are breached by
joints, fractures, collapse features, or other structural anomalies. Examples are displayed in
Figure 1 (bottom).

During the 1999-2002 drought, the flows in many springs decreased, and one spring
(Hornsby Spring) stopped flowing altogether for a period of time. In addition to the decreased
rainfall, there was an increased demand for groundwater (Verdi et al., 2006). The drought and
the subsequent lowering of aquifer water levels resulted in decreasing spring flows throughout
the state. The increased demand for groundwater during the drought exacerbated the problem in
some of the springs. The increasing trends in rock-matrix analytes during the drought is an
indication of a reduction in size of the fresh water "lens" underlying the state and an indication
of saltwater encroachment. Because the concentrations of saline analytes increased almost
everywhere in the state during the drought, it is an indication that encroachment occurred on a
statewide scale.

Figure 1. Schematics of freshwater/saltwater transition zone and possible mechanisms
for saltwater/freshwater intrusion. Note Cooper (top) represents the saltwater/freshwater in-
terface in the surficial aquifer system as a transition zone, whereas Spechler (bottom) depicts it
as a sharp boundary.

xvii

0 .. .
..*.*.:.';..& *

The 1998-2002 drought was one of the worst historical droughts to affect Florida (Verdi
et al, 2006). Except for south Florida, during the drought the deficit rainfall ranged from about
10 inches in southwest Florida to almost 40 inches in northwest Florida. In order to make up for
the drought, groundwater pumping increased, largely for irrigation (Verdi et al., 2006). Because
an increase in groundwater pumping occurred during one of worst droughts, it is likely that
human-induced saline intrusion took place and contributed to the increase in saline and rock-
matrix analyte trends. On a statewide scale, the extent and severity of the intrusion is difficult to
quantify. However, within the northern portion of the SWFWMD, a water budget and a regional
groundwater flow model indicated that the increase [0.3 cm/yr (+0.1 in/yr)] in groundwater
withdrawals was less than 2.0% of the decline in recharge due to the decrease [18.3 cm/yr (7.2
in/yr)] in rainfall (Ron Basso, Southwest Florida Water Management District, personal
communications). Nevertheless, intrusion should be a concern. If another drought of this
magnitude occurs, depending on the amount of increased pumping, it could potentially have
adverse effects on the long-term sustainability of Florida's groundwater resources.

Nutrients

The Florida Springs Task Force (2000) indicated that Florida's springs face serious
threats due to rapid and continuing population growth. The state's increasing population has
resulted in extensive land-use changes, increased demand for freshwater, and an increased use of
fertilizers. As rainfall seeps through the soils, and moves the nutrients into Florida's underlying
aquifers, it creates localized degradation in Florida's groundwater resources. A report regarding
FDEP's Springs Initiative Program efforts (Florida Department of Environmental Protection, and
Florida Department of Community Affairs, 2002) noted that nitrates have increased since the
1970s. It also noted that over the past 30 years many of Florida's springs experienced an
increase in nuisance algae and invasive exotic aquatic plants. These plants tend to thrive on
excess nutrients and decrease dissolved oxygen levels in spring runs.

Analyses for the 1991-2003 time frame indicated that trends in nutrient concentrations in
Florida's spring-water increased in some springs, while they decreased in others. It is
encouraging to note that there are some decreasing trends. The fact that nutrients (especially
nitrate) tended to increase is an indication that some land-use management practices warrants
reevaluation. But as noted previously, the relationship of these apparent decreasing trends may
be related to diminishing spring flow.

Monitoring

The current study revealed an inverse relationship between rock and saline indicators and
spring flow. The relationship was observed across the state (Figure 2). Note that changes in
spring-water quality often lag behind changes in spring flow. For detail, the smaller charts
depicted in Figure 2 have been enlarged and can be found in Appendix A.

Historically, the WMDs and the USGS have monitored spring-water quality and
discharge. With the commencement of the Springs Initiative, FDEP joined in the monitoring
efforts. Considerable efforts were made to eliminate inconsistencies in monitoring activities.
Unfortunately, at the beginning of the study, the efforts were not always successful. Specifically,
the WMDs, USGS, and FDEP did not always monitor the same analytes, use the same laboratory

xviii

analytical methods, or collect flow data on the same date as chemical and biological data were
collected. In addition, they often sampled at different frequencies. All these inconsistencies
made statewide comparisons very difficult. The results of this investigation demonstrate that
statewide monitoring must continue. For this reason, it is hoped that, in the future, the state can
find ways to minimize monitoring inconsistencies.

Recommendations

One of the most surprising and most significant observations of this study was that rock-
matrix and saline analytes were increasing almost everywhere in Florida's springs, especially
during the drought of Sequence C (1998-2003). Saltwater encroachment is a hugely significant
issue. Saltwater can restrict water use and negatively affect freshwater ecology, and can
adversely affect the long-term term sustainability of Florida's water resources. The relationships
among rainfall, recharge, groundwater withdrawals, groundwater quality and levels, plus spring-
water flows warrant further research, as does the effects of global climate change.

The concentrations of at least one nutrient (nitrate) in numerous springs have been
excessively increasing since the 1970s (Florida Department of Environmental Protection and
Florida Department of Community Affairs, 2002). One of the most visible changes in spring-
water quality has been the increase in nuisance algae and invasive exotic aquatic plants. What is
the relationship between the increases in nutrients and the nuisance plants? Further research is
needed. In addition, land-use management practice modifications are needed in order to reverse
the increasing trends. It is beyond the scope of this study to elaborate on the management
strategies. For a detailed discussion of many of the available strategies, an excellent reference is:
Protecting Florida's Springs Land Use Planning Strategies and Best Management Practices
(Florida Department of Environmental Protection and Florida Department of Community
Affairs, 2002).

Spring-water quality is sensitive to changes in spring flow and to aquifer water levels.
Springs represent excellent natural sampling locations for monitoring saline encroachment. It is
recommended that, to the extent practical, springs should be incorporated into a statewide
saltwater encroachment monitoring network. The results of the spring monitoring could then
potentially be used to supplement well monitoring networks that are often used for saltwater
encroachment purposes.

Although the monitoring of springs and wells is critical for the sustainability of Florida's
water resources, not all analytes of concern are sampled. Synthetic organic, other supplementary
analytes supplementalss), as well as biological indicators, should be included on the monitoring
lists. It should be understood that supplementals are expensive to collect and analyze, and for
these reasons, they can only be sampled on a low frequency basis. It should also be noted that
supplemental monitoring is often determined by site-specific issues. For example, pesticides
may only be detected at certain times of the year or in certain locales, determined by land use
conditions. Supplementals such as pesticides, synthetic organic compounds, and trace metals
should occasionally be sampled.

Figure 2. Inverse relationship of flow to rock and salinity indicator concentrations. Darker
lines represent water levels (whether by stage or spring flow); lighter lines represent saline or
rock-matrix indicators (sodium or alkalinity). Time axes vary. The graphs indicate reciprocity
between decreases in water levels and increases of salinity, regardless of location in the state.
Florida's spring-water chemistry shows a high sensitivity to changes in flow (See Appendix A
for enlarged versions of inset charts).

XX

It is critical that evaluations of spring water and groundwater be clearly disseminated to
the public as efficiently as practical. One efficient method is the use of indices. Stock exchange
indices have been used in the financial community for many years. Groundwater quantity
indices are used by the Edwards Aquifer Authority in Texas. As an example, the authority use
real-time water levels in the Bexar County Index well as an index (indicator) for the entire
county. During dry times, as water levels fall, water restriction measures may be invoked by the
authority. When water levels rise, the restrictions are lifted (Edwards Aquifer Authority, 2006).
There are several potential indices that could be developed for use in Florida. If one or more
indices were developed, they have the potential to become very useful in informing the public
about the status of our springs. However, in order to be viable, buy-in by both the public and
scientific communities are essential. Hopefully, indices will be adopted in the future.

It is essential that technical reports regarding the results of analyses be generated
frequently and in a relatively short time frame. It is acknowledged that it takes a considerable
amount of time for an initial report to be generated. However, after the initial report, the lag time
between sample collection and report generation should reduce considerably. In addition,
subsequent reports using similar interpretative methods could employ computer programs to
create "boiler plate" reports as quickly as analytical data are received from a laboratory.

Standardized spring and well sampling throughout the state is a critical need. If
standardization is achieved, analyses of trends in the future will be much easier to conduct. This
in turn will make the resulting interpretations more comprehensive, and the dissemination of the
interpretive results will be more meaningful to the public. Specific aspects of the standardization
effort include: core and supplemental water-quality analytes and indicators, data reporting,
sampling and laboratory quality assurance, data management, data analysis, and assessment
reporting,

Recommendation Synopsis

Research

Determine the relationships between increases in nutrients and nuisance plants/algae

Determine the best land-use management practice needed in order to reverse increasing
nutrient trends

Florida is blessed with some of the most spectacular springs in the world. There are
estimated to be over 700 springs in the state. People have been attracted to our springs since
before Florida became a state. From a scientific perspective, some of Florida's springs have
been sampled for over a century. The FGS published its first Springs of Florida bulletin
(Ferguson et al., 1947), which documented the chemical and flow data of the major springs. The
bulletin was revised in 1977 (Rosenau et al., 1977) and a new bulletin was generated in 2004
(Scott et al., 2004). In each revision, additional chemical data were presented. Unfortunately, as
beautiful as the springs are, not all is well. As Florida's population continues to grow, water-use
and land-use changes are reflected in our spring water. The quantity and quality of spring water
are both changing, and at least some of the changes are directly related to human activities.

Since the 1940s Florida's population has grown from about two million to about 18
million in 2000. This means that Florida has increased its population by a rate of about 600
people per day for those 60 years. In fact, between the years 2000 and 2005, the net rate of
increase has been over 700 people per day (U.S. Census Bureau, 2006). In the year 2000,
Floridians withdrew 3.14 billion gallons of groundwater daily (Marella and Berndt, 2005).
Marella and Berndt (2005) indicated that agriculture and public supply accounted for over 82
percent oft he groundwater use. Based on these data, each person used over 150 gallons per day
of groundwater. It is not surprising that an extensive increase in water use has followed
Florida's population growth. Neither is it surprising that there has been a noticeable decline in
the discharge of many of Florida's springs and that the intensive land-use changes have been
followed by a noted deteriorations in spring-water quality. Scott et al. (2004) mentioned that one
of the most notable deteriorations has been the increase in nutrient concentrations in spring
water. While nutrients such as nitrogen and phosphorous are required by aquatic organisms for
growth and reproduction, when the concentrations are found to be higher than natural levels,
problems can arise. Since the 1970s, concentrations of nitrate, a soluble form of nitrogen, have
been found to be increasing in a number of Florida springs (Florida Springs Task Force, 2000).

Over the past several decades, flows in Florida's springs are declining and water quality
is degrading. The primary chemicals of concern are nutrients, including soluble forms of
nitrogen and phosphorus.

In order to improve and protect our springs, the Florida Springs Task Force (2000) made
a series of recommendations to the Governor of Florida. One was that Florida should implement
spring monitoring programs in order to detect and document long-term trends in water quality.
In addition, it was recommended that the state should conduct research in order to determine the

FLORIDA GEOLOGICAL SURVEY

cause-and-effect relationship between land-use and water-management activities, and the
resulting changes in spring-water quality and quantity.

As a result of the Florida Spring Task Force's first recommendation, the FGS was asked
to evaluate historical spring data in order to detect and document trends in spring-water quality
and quantity. This document reports the findings of analyses for trends in springs, using data
from the Springs Initiative of FDEP, the WMDs, and the USGS spring sampling programs.

ACKNOWLEDGEMENTS

The authors wish to acknowledge a number of individuals and to thank them for their
assistance. From the Florida Department of Environmental Protection, Division of
Environmental Assessment and Restoration, Bureau of Watershed Management, we would like
to thank Gail Sloane and Jay Silvanima for supplying the authors with data from the TV Network
and their miscellaneous assistance on numerous occasions. Laura Morse assisted in supplying
quality assurance information. Debra Harrington, Rick Hicks, Gary Maddox, Jay Silvanima,
Chris Sedlacek and Paul Hansard (now with the Colorado School of Mines) supplied numerous
editorial comments during the course of the project. From the FGS, we would like to thank
Doug Calman, Rick Green, Tom Greenhalgh, Harley Means, Frank Rupert, Tom Scott, and
especially Ellen McCarron, for their many helpful editorial comments.

We would also like to acknowledge the efforts of numerous people from the water
management districts who supplied us with spring data and constructive comments regarding the
document. In particular the authors would like to thank Kris Barrios, Angela Chelette, Tony
Countryman, Kevin De Fosset, Tom Pratt, and Nick Wooten, from the Northwest Florida Water
Management District (NWFWMD); Ron Ceryak and David Hornsby of the Suwannee River
Water Management District (SRWMD); and Ron Basso, Eric DeHaven, David DeWitt, Joe
Haber, Robert Peterson, and Roberta Starks from the SWFWMD.

We would like to thank Brian Katz and Stuart Tomlinson of the USGS. Both individuals
supplied data and other information that was invaluable to the project. We would like to thank
Dr. Xu-Feng Niu of the Florida State University, Department of Statistics, for contributing to the
section regarding statistical methodologies and to Rich Smith, a graphic designer, who assisted
with making many of the figures.

FLORIDA'S SPRINGS

Scott et al. (2004) presented an excellent overview of Florida's springs. Although they
did not specifically evaluate trends, the authors described hundreds of Florida's springs,
including a description of their water quality. In doing so they described many aspects that
control the water quality and quantity of groundwater. With this in mind, their work can be
considered a precursor to the present trend analysis document. With the authors' permission,
much of the following introduction from the sections labeled "Florida's Springs" to "Differences
in Spring and Well Water Quality" are paraphrased from their work, "Springs of Florida."

BULLETIN NO. 69

Many terms relating to hydrogeology and springs may be unfamiliar to the reader. For this
reason a glossary of terms is found in Appendix B 1. In addition, Appendix B2 elaborates on the
sources of the analytes discussed in this report, along with the probable causes for the trends
observed.

Spring-water discharge comes primarily from the Floridan aquifer system, which is also
the state's principle source of groundwater. The springs provide a "window" into the aquifer,
allowing for a measure of the health of the aquifer. Chemical and biological constituents that
enter the aquifer through recharge processes may negatively affect the water quality in aquifers,
as well as the flora and fauna of springs and spring runs. The declines in water quality can be
directly attributed to Florida's increased population and changing land-use patterns (Florida
Springs Task Force, 2000).

Classification of Springs

Springs are most often classified on the amount of flow or discharge of water. The flow-
based classification listed in Table 1 is taken from Meinzer (1927) (Table 1). One discharge
measurement is all that is required to place a spring into one of eight magnitude categories.
However, it should be understood that each spring exhibits a variable discharge, depending upon
rainfall, recharge and groundwater withdrawals within their recharge areas. This can result in a
spring being classified as a first magnitude spring at one point in time and a second magnitude at
another. In the past, a spring assigned a magnitude when it was first described and continued
with that magnitude designation even though the discharge may have changed considerably over
time. To alleviate this confusion, the FGS (Copeland, 2003) adopted a system using the
historical median of the flow measurements to classify a spring's magnitude. Using the new
system along with the Meinzer system, a spring's magnitude is now based on the median value
of all annual median discharge measurements for the period of record. Of the over 700 springs
inventoried by the FGS, there are 33 first-magnitude springs, 191 second-magnitude, and 151
third-magnitude springs. Most are located in the northern portion of the state (Figure 3).

A second spring classification system is also in use. The Florida Spring Classification
System (Copeland, 2003) (Table 2) is based on an assumption that karst activities have
influenced almost all springs in Florida. Under this system, all springs in Florida can be
classified into one of four categories, based on the spring's point of discharge. Is the point of
discharge a vent or is it a seep and is the point of discharge located onshore or offshore? Since all
springs are either vents or seeps, the classification can be simplified into the following
categories.

A spring vent is defined as an opening that concentrates groundwater discharge to the
Earth's surface, including the bottom of the ocean. The opening is significantly larger than the
average pore space of the surrounding aquifer matrix. A vent is occasionally considered to be a
cave, and groundwater flow from this type of vent is typically turbulent. On the other hand, a
spring seep is composed of one or more small openings in which water discharges diffusely (or
"oozes") from the groundwater environment. The diffuse discharge originates from the
intergranular pore spaces in the aquifer matrix. Flow from seeps is typically laminar.

BULLETIN NO. 69

Offshore Springs

Springs occur both onshore and offshore in Florida. Currently, little is known about the
offshore, or submarines springs, with the exception of the Spring Creek Group-the largest spring
group in Florida, averaging more than one billion gallons of water discharged per day (maximum
flow estimated at more than two billion gallons of water per day [Rosenau et al., 1977; Lane,
2001]). Offshore or submarine springs (Figure 4) are known to exist off Florida's Atlantic and
Gulf of Mexico coastlines. These springs are most common in the offshore portion of Florida
from Crystal Beach Spring (Figure 4, Spring No. 7) to Bear Creek Spring (Figure 4, Spring No.
1). Offshore springs have also been identified off the northeastern and southwestern parts of the
Florida and the western panhandle (Rosenau et al., 1977) (Figure 4). Water-quality data from
some of these springs indicate that, at best, the water is brackish. There are anecdotal reports of
"fresh water" flowing from Florida's offshore springs.

In addition to the awareness of increasing trends in contaminants such as nitrate over the
past several years (Figure 5), there has also been an increased awareness on the drainage basins
that supply water to Florida's groundwater and springs. The amount of water and the nature and
concentrations of chemical constituents that discharge from springs are functions of the geology,
hydrology, weather conditions and land uses within the spring recharge basin. This type of basin,
often referred to as a springshed, consists of those areas within groundwater and surfacewater
basins that contribute to the discharge of the spring (Dehan, 2002; Copeland, 2003). The
springshed consists of all areas where water can be shown to contribute to the groundwater flow
system that discharges from the spring of interest. Karst systems frequently include sinking
streams that transmit surface water directly to the aquifer; the recharge basin may include surface
water drainage basins that bring water into the spring drainage from outside of the groundwater
basin.

Florida enjoys a humid, subtropical climate throughout much of the state (Henry, 1998).
Rainfall, in the region of the major springs (Figure 1), ranges from 127 cm (50 inches) to over
152 cm (60 inches) per year. As a result of the climate and the geologic framework of the state,
Florida has an abundant supply of fresh groundwater. Scott (2001) estimated that more than 8.3
billion cubic meters [2.2 quadrillion (2.2 x 1012) gallons] of freshwater are contained within
Florida's aquifers. However, only a very small percentage of freshwater is available as a
renewable resource for human consumption.

The Florida peninsula is the exposed portion of the broad Florida Platform. The Florida
Platform, as measured at the 200 meter (more than 600 ft) below sea level contour, is more than
483 km (300 miles) wide. It extends more than 240 km (150 miles) westward under the Gulf of
Mexico, and more than 113 km (70 miles) under the Atlantic Ocean. The present day Florida
peninsula is less than one half of the total platform.

The Florida Platform is composed of a thick sequence of variably permeable carbonate
sediments, limestone and dolostone, lying on older igneous, metamorphic and sedimentary rocks.
The Cenozoic carbonate sediments may exceed 1,220 m (4,000 ft) thick. A sequence of sand, silt
and clay with variable amounts of limestone and shell overlie the carbonate sequence (see Scott
et al, 1991 and Scott, 1992b for discussion of the Cenozoic sediment sequence and the geologic

FLORIDA GEOLOGICAL SURVEY

structure of the platform). In portions of the west-central and north-central peninsula and in the
central panhandle, the carbonate rocks, predominantly limestone, occur at or very near the
surface. Away from these areas, the overlying sand, silt and clay sequences become thicker. As
the rocks sediments compacted and were subjected to other geologic forces, fractures formed.
These fractures allowed water to move more freely through the sediments and provided the
template for the development of Florida's many cave systems.

There are three major aquifer systems in Florida, the Floridan, the intermediate and the
surficial aquifer systems (Southeastern Geological Society, 1986; Scott et al., 1991). The
Floridan aquifer system (FAS) occurs within a thick sequence of permeable carbonate sediments
(see Miller, 1986 and Berndt et al., 1998 for discussion of the FAS). In some areas, it is overlain
by the intermediate aquifer system (IAS) and the intermediate confining unit (ICU) which
consists of carbonates, sand, silt and clay. The surficial aquifer system (SAS) overlies the IAS
(or the FAS where the IAS is absent), and is composed of sand, shell and some carbonate. The
vast majority of Florida's springs result from discharge from the Upper Floridan aquifer system
(UFAS), a subdivision of the FAS as discussed by Miller (1986).

Typical natural recharge to the FAS originates as rainwater. As the acidic rainwater
percolates downward to the FAS, it is made slightly more acidic by carbon dioxide from the
atmosphere and organic acids in the soil. Once in the FAS, the groundwater dissolves portions
of the limestone and enlarges naturally occurring fractures. The dissolution enhances the
permeability of the sediments and forms cavities and caverns. Sinkholes are formed by the
collapse of overlying sediments into the cavities. Occasionally, the collapse of the roof of a cave
creates an opening to the land surface. See Lane (1986) for a description of sinkhole types
common in Florida.

Recharge to the FAS occurs over approximately 55 percent of the state (Berndt et al.,
1998). Recharge rates vary from less than 2.54 cm (one inch) per year to more than 25.4 cm (10
inches) per year. Water entering the upper portion of the FAS eventually discharges from a
spring. The water has variable residence times. Katz et al. (2001) and Katz (2004) found that
water flowing from larger springs had a mean groundwater residence time of more than 20 years
and may reflect the mixing of older and younger waters.

Florida's springs occur primarily in the northern two-thirds of the peninsula and the
central panhandle where carbonate rocks are at or near the land surface. Most of these springs
produce water from the UFAS which consists of sediments that range in age from Late Eocene
(approximately 36 38 million years old [my]) to mid-Oligocene (approximately 33 my).
Miocene to Pleistocene sediments (24 my to 10,000 years) often are exposed in the springs.

The geomorphology of the state, coupled with the geologic framework, controls the
distribution of springs. The springs occur in areas where karst features (for example, sinkholes
and caves) are common, the potentiometric surface of the FAS is high enough and the surface
elevations are low enough to allow groundwater to flow at the surface. Springs generally occur
in lowlands near rivers and streams. There are a number of springs known to flow from vents
within river channels and many more are thought to exist. Hornsby and Ceryak (1998) identified
many newly recognized springs in the channels of the Suwannee and Santa Fe Rivers. Springs

BULLETIN NO. 69

that have yet to be described have been found within the Apalachicola River between Gadsden
and Jackson Counties (H. Means, Florida Geological Survey, personal communication, 2004).

Weather and climatic events affect the appearance of spring water. For example, during
periods of higher than normal precipitation, such as hurricanes, some springs may reverse flow.
When this occurs, stream water flows into the aquifers. During these times, spring water often
has a dark appearance because of the presence of tannins from surfacewater sources. Once
stream levels drop enough, the dark waters again reverse flow. When this occurs, discharge
becomes much clearer. Dryer periods also affect the appearance of springs. For example, during
1998 2002, Florida experienced a major drought with a rainfall deficit in places totaling more
than 127 cm (50 in) (Verdi et al., 2006). The resulting reduction in recharge from the drought,
along with the normal withdrawals, caused a lowering of the potentiometric surface in the FAS.
Many first magnitude springs experienced a significant flow reduction. Some springs ceased
flowing completely. The appearance of the springs also changed as river and lake levels
declined reducing the size of the spring-water body and exposing sediments along the banks.

QUALITY OF GROUNDWATER AND SPRING WATER

Natural Factors Affecting Groundwater and Spring-Water Quality

Most of the Florida land mass is a peninsula that is surrounded by saltwater. Relict
saltwater also underlies the entire state. The reason for this is that the Florida Platform consists
of carbonate rocks that were deposited in a shallow ocean. At the time of deposition, saltwater
existed in their intergranular pore spaces. Gradually over geologic time, sea level was lowered
relative to its position when the carbonate sediments were deposited. Through compaction and
down warping of sediments on both sides of the Platform, a series of complex fracture patterns
developed. The patterns are often reflected at land surface and have actually influenced the
pathways of many of Florida's streams.

Over geologic time, as sea level lowered, the central portion of the Florida Platform was
exposed to the atmosphere. As rainfall percolated downward it eventually replaced the upper
portion of saltwater in the developing aquifers with a freshwater "lens." Today, the irregularly
shaped "lens" is generally thickest in the central portion of the state, where it is over 610 m
(2,000 ft) thick (Klein, 1975). It becomes narrow toward Florida's coastline. The base of the
"lens" is typically a transitional rather than a sharp boundary. Groundwater in the deeper portion
of the "lens", and along the coasts, is mixed with saltwater and has relatively high concentrations
of saline indicators such as sodium (Na), chloride (Cl), and sulfate (SO04).

Water discharging from Florida's aquifer systems and springs has its primary source from
rainfall. Much of the rainfall reaching land surface flows overland to surfacewater bodies,
evaporates, or is transpired by plants. However, a portion of the rainfall percolates downward
through the sediments, or enters sinkholes, where it recharges the aquifers. During its travel
downward from land surface to the water table, and during residence within Florida's aquifer
systems, many factors affect the water chemistry.

FLORIDA GEOLOGICAL SURVEY

A long residence time may allow sufficient time for chemical reactions between the water
and the aquifer rock. As such, water chemistry reflects the composition of the aquifer rock.
Typical residence times range from less than several days (in secondary produced caverns and
sinkholes) to centuries (Hanshaw et al., 1965).

A second factor affecting groundwater chemistry is flow path, which is the length and
depth of the path that the groundwater follows as it flows through an aquifer (Upchurch, 1992).
In general, shallow, short flow paths (which are characteristic of the SAS) result in shorter
residence times for chemical reactions to take place. Consequently, the total dissolved solid
(TDS) content is less than in longer flow-path systems. If the flow path is long (on the order of
tens of kilometers), such as commonly occurs in the FAS, reactions between rock and water
become more probable and the TDS content of the water would be greater as a result of
continued rock-water chemical reactions. Because of the residence time and the flow paths of the
groundwater within an aquifer, the quality of spring water is typically reflective of the
interactions of the major rock types in the aquifer and the groundwater itself.

A third factor which is of particular interest is intergranular porosity (pores through
which water passes between the individual rock matrix grains). Even though Florida's aquifers
have large, secondary cavernous pores spaces, most of the pores tend to be small (Upchurch,
1992). Fortunately, whenever the pores are very small, they act as filters for microbes, small
organic substances, and clay minerals. In general, this results in naturally filtered groundwater
that is very pure and desirable for both drinking water and recreation. Unfortunately, some
pollutants are not always removed and our aquifers can become contaminated.

Differences in Spring- and Well-Water Quality

The processes controlling the water quality in wells is very similar to those controlling
spring-water quality with at least one major difference. Wells are often drilled to production
zones as close to land surface as is economical. This is the situation for the wells used in this
study, which are for the most part monitoring wells. Monitoring wells tend be shallow (median
depth z 80 feet (24 m) (Appendix C). Most water in these shallow wells represents young,
recently recharged water. On the other hand, because springs are major discharge points, spring-
water can be considered to be an integrator of water from the entire springshed. Spring water is
a mixture of young, shallow, freshly recharged water and older water from the deeper portions of
the aquifer. For this reason, spring water tends to be older than the relatively shallow water
found in the monitoring wells used in this study.

Indicators of Groundwater and Spring-Water Quality Problems

Spring water, while it resides in the aquifer, is considered to be groundwater. However,
once spring water exits from the spring onto the earth's surface, it is considered to be surface
water. Because of this change, the question arises whether regulators should apply groundwater
or surfacewater quality standards to the water. Primary and secondary standards with maximum
contaminant limits (MCLs) may exist for an analyte while the water is considered groundwater,
but differ for surface water; or vice versa. Drinking water standards are protective of human

BULLETIN NO. 69

health while surface water criteria are protective of aquatic biota. Although several analytes fall
into this category, Nitrate (NO3 + NO2 as N), and hereafter abbreviated NO3, is a good example.
Based on drinking water criteria, nitrate has a groundwater threshold value of 10 mg/L (Florida
Department of Environmental Protection, 1994). However, no numeric nitrate criteria exist for
surface water, other than Class I surface water which is used for drinking water. The FDEP is
currently developing criteria for spring water. Until legal numeric criteria are established for
nitrates, it should be understood that any reference to threshold values in the following text
simply infers potential water-quality problems.

The natural background nitrate concentrations in Florida groundwater are less than 0.05
mg/L (Upchurch, 1992). During the 2001-2002 time frame, the FGS sampled 125 spring vents.
Of the 125 spring vents sampled, none had nitrate concentrations exceeding the 10 mg/L
threshold for Class I surface and drinking water. Fifty-two of the spring vents sampled had
nitrate concentrations exceeding 0.50 mg/L (42 percent) and 30 (24 percent) had concentrations
greater than 1.00 mg/L. Thus, over 40 percent of the sampled springs had at least a ten-fold
increase in nitrate concentrations above background and approximately one quarter of them had
at least a 20-fold increase. The elevated nitrate concentrations may adversely affect the aquatic
ecosystem in springs and spring runs. Further research is still needed and is currently being
sponsored by the Springs Initiative Program. The FDEP is aware of the nitrate issues and has
worked with other governmental agencies to develop a series of steps to reduce nitrate
concentrations in groundwater and springs in the middle Suwannee River Basin where many of
Florida's springs are located (Copeland et al., 2000). The FDEP Bureau of Watershed
Management and the Florida Department of Community Affairs are active in coordinating the
development of spring protection measures.

Another groundwater quality concern is the influence of saline water. Several springs
have concentrations of chloride (Cl; a saline indicator) exceeding the 250 mg/L threshold for
drinking water. Springs with this type of water tend to be located along Florida's coast and along
the St. Johns River. The ultimate source of the saline indicators is from naturally occurring saline
water within the FAS (Klein, 1975), or from sea water near Florida's coasts. When the
concentrations of saline indicators are increasing, it may be the result of: (1) natural
circumstances such as drought, (2) the consequent upcoming of groundwater within the FAS, or
(3) lateral intrusion of salt water due to increased groundwater pumping.

Enterococcus and total coliform bacteria represent a third concern. It is generally
believed that these bacteria originate in fecal matter from warm-blooded animals (Jelinkova
and Rotta, 1978). Total coliform concentrations in several springs has exceeded the

drinking water standard of four colonies per 100 ml (Florida Department of Environmental
Protection, 1994). However, it has been determined that these bacteria can complete their normal
life-cycle outside of warm-blooded animals, especially in environments found in parts of Florida
(Fujioka and Byappanahalli, 2004), thus the concentrations of fecal coliform may not necessarily
represent a direct link to warm-blooded animal pathogens. Further research is needed before
definitive conclusions can be made regarding the source of fecal bacteria. Another concern is
concentrations of enterococcus and fecal coliform bacteria with regards to swimming. The
Florida Department of Health has set beach swimming standards and advisory thresholds for
both organisms. To date, exceedances of the standards and thresholds in springs have not been a
problem. Nevertheless, many residents swim in spring runs and these bacteria are a concern.

SPRING SELECTION PROCESS

Very little spring-water quality sampling, mostly by the USGS, occurred until the 1940s.
In 1947, the FGS published its first edition of "Springs of Florida" (Ferguson et al., 1947) which
documented the water quality in the major springs of Florida. The document was revised in 1977
and many previously undocumented springs were sampled (Rosenau et al., 1977). It should also
be noted that during the 1970s, the three northern water management districts were formed.
They were the NWFWMD, the SRWMD, and the (Saint Johns River Water Management District
(SJRWMD). Within a few years, these WMDs, along with the USGS and the already established
SWFWMD, occasionally collected spring-water quality samples. By the 1990s, the NWFWMD,
SRWMD, SJRWMD, and SWFWMD had established periodic to regular sampling, often with
the assistance of the USGS, of springs within their jurisdiction.

Partially due to the sampling efforts of the WMDs, in the 1990s it became apparent that
the water quality in some of Florida's springs was deteriorating. For this reason, in 1999 the
Secretary of the Florida Department of Environmental Protection directed the formation of a
multi-agency Florida Springs Task Force to provide recommendations for the protection and
restoration of Florida's springs. In late 2000 the Task Force made recommendations for the
preservation and restoration of Florida's springs to the Secretary, and in 2001 the Florida
Legislature passed the Florida Springs Initiative. The Initiative authorized funds for FDEP to
begin investigating the status of Florida springs and develop strategies for protecting them. As a
result of the Initiative, the four WMDs, FDEP, and the FGS have cooperated to monitor Florida's
springs.

The Springs Initiative has been responsible for the collection of spring-water quality
since 2001. Beginning with that year, much of the data used in this report were obtained from
Springs Initiative-sponsored samples. Methods of evaluating the data used in this report can be
used in the future to analyze the spring data currently being generated as a result of the Springs
Initiative. In the meantime, data of spring-water quality collected as part of WMD spring
sampling programs were used for this interpretative report.

The FGS requested spring data from each of the four northern WMDs in order to analyze
spring-water quality and quantity for trends. The districts delivered available data to the FGS in
2002 and 2003. It was soon discovered the WMDs had only sporadically sampled their springs

BULLETIN NO. 69

through the 1980s. However, beginning in the early 1990s each district had begun to sample
springs in a semi-consistent manner. Even though data do exist for many springs, only 58
springs (Figure 6) were ultimately included in the analysis; one from the NWFWMD, 14 from
the SRWMD, 15 from the SJRWMD, and 28 from the SWFWMD. Selection was determined
based on the consistency of the data. As a working definition, we considered consistency to be
the longest string of data in terms of time, along with the greatest number of analytes. We also
wanted the largest number of springs to be included that met our concept of consistency. With
these criteria in mind we determined that the time period from January 1991 through December
2003 represented the time in which the most consistent data existed for the greatest number of
springs. We realize that there are several springs that have decades of data. We also realize that
since commencement of the Springs Initiative, many springs now have data, but the time
sequences are short. As a result, our data interpretations are valid only for the 1991-2003 time
frame.

A discussion of analytes evaluated and frequencies of sampling will be discussed later.
Figure 6 displays the location of the included springs in the analyses. A list of the names of
springs, along with location information, can be found in Appendix D.

WELL SELECTION PROCESS

In 1983, the Florida Legislature passed the Water Quality Assurance Act (Florida
Statutes, 1983, Chapter 403.063). As a result, FDEP, with the assistance of the five water
management districts, plus several counties (Alachua, Broward, Collier, Lee, Miami-Dade, and
Palm Beach) established extensive groundwater monitoring networks. The purpose was to
document both ambient groundwater quality conditions (Background Network) and to detect
changes in Florida's groundwater quality resulting from the effects of various land uses and
potential sources of contamination (Very Intense Study Area Network [Scott et al., 1991]). Both
networks were in operation until 2000. A major subdivision of the Background Network was the
Temporal Variability (TV) Network. The TV Network consists of a series of strategically-
located Background Network wells scattered throughout the state. They are sampled on a
monthly to quarterly frequency.

Beginning in 1996, FDEP began a major redesign of its water resource monitoring
efforts. The purpose of the redesign was to characterize the environmental conditions of
Florida's water resources and to determine if those conditions are changing over time. The
revised network (The Status Network) became operational in early 2000. A detailed description
of the Status Network is presented by Copeland et al. (1999). Throughout the redesign process,
the TV Network only had minor modifications. The stated purpose of the redesigned network is
to evaluate temporal variability of Florida's groundwater quality and to determine whether
concentrations of the sampled analytes are increasing or decreasing over time. The TV Network
consists of 46 wells (Figure 7); 25 wells monitor confined groundwater and 21 wells monitor
unconfined groundwater. The wells tap each major aquifer system and are scattered throughout
each of Florida's five WMDs. As can be seen in Figure 7, some of the well locations represent

FLORIDA GEOLOGICAL SURVEY

N

S

Legend
Springs
NWFWMD
SFWMD
S SJRWMD
S SRWMD
S SWFWMD

"%- %.

'*
;...-&

.A~: ~

Miles

0 30 60 90

Kilometers
0 70 140 210

Figure 6. Location of springs analyzed in this report. (A list of the spring names can be found in
Appendix C.)

BULLETIN NO. 69

N

S

Legend
Wells
NWFWMD
SFWMD
M SJRWMD
I SRWMD
I SWFWMD

., -

Miles
0 50 100 150

Kilometers
0 75 150 225

Figure 7. Location of Temporal Variability Network (TVN) wells. (A list of well identifiers can
be found in Appendix D.)

FLORIDA GEOLOGICAL SURVEY

clusters of wells. Wells that monitor confined ground water are sampled quarterly (thought to
have less temporal variability), whereas wells that monitor unconfined groundwater are sampled
monthly.

With respect to the WMDs, the NWFWMD has eight wells, the SRWMD has 10 wells,
the SJRWMD has nine wells, the SWFWMD has 11 wells, and the SFWMD has eight wells in
the TV Network that had significant data for analyses. A list of well names can be found in
Appendix C, along with well construction data.

METHODS

This report uses a relatively simple methodology to determine the condition of spring and
groundwater quality. Most analyses boil down to the single straightforward question, "are
conditions getting better, getting worse, or remaining the same?" Though this report is based
upon several statistical procedures, all address this single question.

With this simple objective in mind, additional elaboration is required to expand upon the
connection with actual statistical tests and methods. First, since "better" and "worse" are
subjective and qualitative questions, an approach that will quantify them is needed. Thus, a
somewhat more objective and quantitative form of the above question becomes, "for the 1991-
2003 period of record, are the indicators decreasing, increasing, or remaining the same?" This
frames the question of quality in the terms of changing quantities between two end-points (i.e.,
the start and finish of a time period of interest); changes in quantities, such as flow and loading,
can be objectively tested in a variety of ways.

In order to test quantities, the last remaining questions are: (1) which quantities and, (2)
over what period of time? These further conditions must be defined. The first question is which
quantities? For this report, as many indicators as possible were tested. This allowed the authors
to ask questions of the largest possible scale; limiting the number of indicators only limits the
possible number of observations and maximizing the number of observations allows the most
comprehensive view of changes that might be of concern. Second, for the quantities examined an
increase or decrease in concentration must be addressed over a time frame. Therefore, in order to
maximize the effectiveness of the analysis, the longest possible time series was chosen for as
many springs as possible. In summary, the choice was for the longest possible time frame for
data il ith the highest quality, for as many indicators possible, and for as many springs as
possible. Laboratory and collection methodologies have varied over the last several decades in
the state of Florida. Variations include not only differences among WMDs, but even use of
different laboratories by the same district, changes within laboratories, incomplete sampling
intervals due to varying purposes and other reasons. Because of this, the earliest starting point for
which data quality could be uniformly assumed to be high (in this case 1991) was chosen; this
created the longest possible time series for analysis (1991-2003) for as many springs as possible.

Regarding the second question, for this report, we chose trend analysis to evaluate a
given time series (between 1991 and 2003) for linear trends. Note that Urquhart and Kincaid
(1999) mentioned that trends may deviate from strict linearity. Nevertheless, they mentioned

BULLETIN NO. 69

that if a trend is present, a linear trend will be present, regardless of the type of mathematical
structure of the trend, e.g. cyclic, episodic, or a stair-step look.

For this report, we were not only interested in detecting the presence of a trend we were
also interested in a statistical method that was relatively insensitive to missing sampling points
(e.g., gaps in data series), outliers, and, data that seldom had normal (Gaussian) distributions.
Based upon these reasons, our choice for analysis was the non-parametric, Mann-Kendall (MK)
test for trends. Discussions of the MK test and other statistical procedures used in the study,
including the corresponding assumptions, are found in Appendix E.

Our last clarification involves interpretation of trends; not all increases are bad nor are all
decreases good. For example, a decrease in nitrate is desirable and is considered to be good. On
the other hand, a long-term decrease in flow is not desirable, since it may indicate an overuse of
the resource. Thus, it can be considered to be bad. Another example, an increase or decrease in
pH may not be considered to be good (if it is extreme), since this analyte is best defined by an
optimal middle range; being far outside that range on either side is bad. The point is that change,
in one direction or another, can be tested and the result has implications regarding the
improvement or degradation of the system in question.

Definition of Trends

Natural systems in general undergo two main types of change: cyclic and linear (A and B,
top of Figure 8). Cyclic change is common in nature. Two common examples of cyclic changes
include diurnal and seasonal changes. Natural changes can also be linear, moving conditions
from one state to another without returning to the original state. The focus of this report is to
document linear trends in water quality and quantity. It is also assumed that trends in certain
analytes are most likely anthropogenic, rather than natural in origin. In this case, three possible
linear trend scenarios can be tested. In each case, a chemical component of a groundwater system
(whether spring or well) can be plotted as a concentration against time (Figure 8, bottom). The
first scenario (on the left) is that the system is increasing in concentration for a particular analyte
(for which the symbol, "+", will be used in this report). One case could be phosphorus. Over a
period of interest, change of concentration can be tested at a specific level of confidence (e.g., at
a 95 percent confidence level, or an a level of 0.05). This means that by the end of the time
period, the concentration was high enough to warrant the designation of being higher than
expected by chance fluctuation alone. Such values are marked as being highly unlikely to have
occurred unless notable changes to the system were introduced. In the opposite case (on the
right), the concentration could have decreased significantly (represented by "-"). Such a trend
suggests a substantial change to the physical environment and would therefore be recorded. The
third scenario (middle chart) is that neither case was observed. As will be detailed below, this is
not a positive statement affirming uniform conditions for the system in question; rather it is a
general category for all conditions not classified within the former two situations. This is a
default option and it is likely that a number of valid trends that could escape detection and be
included in this scenario.

FLORIDA GEOLOGICAL SURVEY

/

3 observations for trends:
Increasing Trend (+) Unable to confirm

Decreasing Trend (-)

Time

Figure 8. Illustration of three options for water-quality trends. Trends can either increase (+), decrease (-), or
otherwise cannot be confirmed. Depending on the analyte, the interpretation is that the system is getting better,
getting worse, or remaining the same. Taking the example of phosphorus, if the trend is increasing, the situation is
getting worse. If the trend is decreasing, it is getting better. Finally, if neither, nothing can be confirmed. All
analyses in this report are assigned to one of these three observations.

Problems with Trends

Trend analyses were largely straightforward and posed few problems. Visual analysis of
time series plots showed that the majority of significant trends were based on a large amount of
data that indeed demonstrated an obvious tendency. However, several exceptions arose and their
handling is addressed in the following sections.

"Remaining the Same" Possibility of Missed Trends

The last case scenario in the phrase "getting better, getting worse or remaining the same"
leaves a question as to the identity of the last category. Note that the last observation-
"...remaining the same"-cannot be addressed statistically. It is, therefore, considered the
alternative case to the situation of an increasing or decreasing trend. Because of this
"... remaining the same" amounts to a catch-all for all remaining observations (i.e., trends that
neither increased nor decreased). Though simple in principle, a clarification should be stated.
Within this last category remains interesting, important, and valuable information-cycles,
interesting structure, nonlinear trends, or other phenomena. More problematic, it is likely the
analyses conducted here "missed" a number of trends (due to the strict confidence limit).

However, it is important to state once again that the purpose for this study was neither to find all
the trends possible, nor to find the largest number of trends; rather, the purpose was to identify
all the trends that could be confidently, statistically labeled as such. Other studies employing
greater power (i.e., ability to detect more trends) could, and probably should, be conducted. But
since this is the first such statewide analysis of water-quality trends, the goal was to minimize the
number of false trends-while maximizing the number of true trends-in order to get the best
picture of where the clearest problems exist.

Outliers

Statisticians often encounter data that lies outside of an expected range of values. The
reasons for this may include data transmission errors, failed laboratory analyses, contaminated
samples, and sometimes accurate data recording unusual situations-causes are not always
visible to analysts. This report was no exception. Technically, there are really only two ways of
dealing with such data. One is to set arbitrary guidelines in advance and handle the data in
accordance. This may include removing outliers that occur above or below a certain accepted
range, e.g. adjust the data. The other approach is to include all outliers in the dataset and
analyze the data regardless. The rationale is that well-maintained data sometimes records outliers
but, with sufficient data, the effects will be minimal. This report chose the latter option and
included all data in all analyses-none were discarded. Their presence was accounted for and
accommodated in several ways. The first was simply by the choice of analysis. Nonparametric
statistics are relatively insensitive to the influence of extreme data points (outliers).

A large number of "bad" data points can still influence even a nonparametric analysis.
Cross-checking results and examining raw data can assist with this judgment. In order to
compare and check the influence of outlying data, every nonparametric statistical trend test [the
Mann-Kendall (MK) will be discussed later] result was checked against a linear regression
parametricc test) of the same data. Further, both analyses were conducted with different
statistical packages: Minitab (Minitab, 2003) for MK and S-PLUS (S-PLUS, 2003) for cross
checking regression analyses. Visual examination of each individual time series was conducted
to corroborate the results of the statistical tests; suspicious data sets were re-analyzed.
Inspections revealed that in the vast majority of cases, reported statistical trends were composed
of time series that showed clear visual trends. Comparison of MK results to linear regressions
(though parametric) showed surprising similarity. Not only did the non-parametric MK results
closely match the parametric analyses, but both were surprisingly unaffected by outliers; thus
providing strong confirmation that both the data was of high quality and that it gave robust
signals.

Detection Levels

Though the data used in these analyses were the best available in terms of quality
assurance, other factors had to be considered. The analysis of outliers demonstrated that
consistency of data handling, laboratory reporting, and subsequent quality assurance was good.
Yet an additional issue surfaced in the plotted time series: the effect of laboratory detection
limits. For statistical purposes, if a sample's concentration was below the laboratory's method
detection limit, it was considered to be the detection limit. For example, where improvements in

FLORIDA GEOLOGICAL SURVEY

laboratory methodologies over time lowered the minimum detection value for several analytes,
trend analyses detected significant downward trends where no such trend existed. Indeed, a
number of time series plots revealed that a number of trends-statistically significant by MK
tests-were actually the artifact of such "stair step" patterns trending down over time (Figure 9).

All data series, therefore, were checked visually for such spurious results. Those data
series found exhibiting such results were removed from consideration in the final analyses.
These were assigned the designation "DL" (detection level) in result tables (e.g., "plus-minus"
charts which will be discussed later); trends created by detection level artifacts were removed
from further analysis.

Well 1943: Example of Detection Limits

U.UU I I I I I
2/12/1990 11/8/1992 8/5/1995 5/1/1998 1/25/2001 10/22/2003
Date

Figure 9. Example of a spurious trend. Detection limit changes can
generate the appearance of false trends. All time series for all analytes
were visually checked for aberrant results since visual inspection was
was necessary to identify artifacts.

HII EEElllI

BULLETIN NO. 69

Sparse Data

The quantity and consistency of existing data varied widely depending on sampling
agency, analyte, and location of springs or wells. Given the amount of data used for the time
series studied herein, a distinction should be made concerning how the quantity of data affected
its quality. First, all reported analyses had sufficient data for time series analysis. Sufficient data
constituted a minimum of 10 points for the entire series. Many software packages would not
generate statistical results without a minimum set of points-which was often 10 values. At the
same time, there is a difference between what constitutes a sufficient amount of data and how
that (sufficient) quantity is structured through time. The former issue concerns whether an
analysis could be conducted while the latter has implications for the reliability of the
interpretation. On one end of the spectrum, some locations only had 10 values, while at the other
some had in excess of 100 values. As it turns out, considering both springs and wells, the
median number of data for the 1991-2003, Sequence A, time frame was 38.

Long-term, consistent data collection is an ideal situation for analysis. However, most
data sets were between the extremes of a lot or too little. Much of the data used here can be
described by the term "sparse data" which we use to mean there are not very many data points in
the time sequence but there were a minimum of ten. Often the spring data were collected for
some other purpose than for time-series analysis having little structure at all. This results in
"messy data." Messy or disorderly data includes missing values, outliers, transcription errors, or
extreme and skewed results. Simply stated, a high proportion of time sequences have varying
amounts of missing data. The missing data hinders reliable data interpretation. One example of
"messy data" is nitrate concentrations at Wakulla Spring (Figure 10). An example is as follows.
Suppose a large number of data points exist at the beginning of the time series, nothing in the
middle, and one point at the opposite end of the series. Also, suppose a trend is detected. The
problem with such a trend is that although it is statistically valid, it may be entirely dependent
upon the single point at the one end of the series. If such a trend is labeled valid, then poor
judgment was used. The best interpretation for a trend exists when there is an abundance of
points sampled consistently for the longest period of time.

Time gaps in data series were the most common problem. In a number of cases data
collected early in the time series were followed by one or more data collection gaps of varying
temporal duration. Such trends are dependent upon the connection of two (occasionally more)
clusters of data. Though the trends may be valid, they are not ideal; this example underscores the
necessity for sampling agencies to implement consistent collection plans over the long term.
Though the data can often be used, its utility can be challenged, or considered suspect. The
reason is that the value of any individual data point is a function of the number and reliability of
nearby data points to which it can be compared over the long term. Data that are sparse,
inconsistently collected, or have large time gaps are substantially less valuable than a consistent,

FLORIDA GEOLOGICAL SURVEY

Wakulla Spring Time Sequence A (1991-2003)

1.1 * U

1.0 U

o" 0.8 y ----
0-

0.6

0.5

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Date
Figure 10. Example of sporadic, unsystematic, and incomplete sampling.
Only seven points were collected in the final eight years of this Wakulla Spring
study. Sparse, inconsistent sampling after 1994 meant the trend seen here was
dependent on relatively few points collected in 2000. Though the trend is statis-
tically valid, this is an excellent illustration of the need for consistent long-
term data collection. Ironically, though budget issues are often responsible for
gaps in sampling, note that missing data greatly reduces the value of points
remaining. Note no data were obtained after 2001 even though Sequence A
continued through 2003.

well-documented time series. Sparse data collection was a significant issue in several notable
springs. For example the trend for nitrate at Wakulla Spring for Sequence A included a six-year
"gap" (1994-2000) during which there was only one sample collected. Although the statistical
conclusion that nitrate concentrations at Wakulla were decreasing is valid (to be discussed later),
with the lack of data during the 1994-2000 time frame, some may doubt the interpretation of a
decreasing trend.

Incomplete data sets existed for many analytes and indicators. Time series for some
analytes (e.g., iron) only had a handful of points over the 13 years. For such very small sets,
trend analysis was meaningless and these were excluded from analysis.

ANALYTES AND INDICATORS

A total of 48 chemical constituents and indicators, with a period of record 1991-2003,
were analyzed for this study. A list of analytes and their corresponding STORET codes can be
found in Appendix F. Data were obtained from several different sources. The state water
management districts offered the most information, followed by FDEP and the USGS. Each
agency used their respective sampling and analysis procedures under whatever guidelines that
were being followed for that particular period of time. This complicated the statistical analyses.
However, identification of useful data led to a field of 48 different analytes of water quality with

BULLETIN NO. 69

a temporal span of 13 years. Table 3 lists, in alphabetical order by column, all of the analytes
examined in this study.

Because many different agencies and laboratories were used to collect and analyze
groundwater samples, unwanted variability was potentially introduced that affected the trend
analyses. At a minimum, potential variability was introduced by: (1) different sampling
personnel, techniques and equipment, (2) sample transport from the field to the laboratory, (3)
environmental and laboratory contamination, (4) concurrent use of several analytical
laboratories, and (5) varying methods of reporting results.

For additional information on the analytes, including abbreviations and units for those 27
analytes that had detectable trends, see Table 4. Spring and well water samples were collected

by several agencies and a private company for the SRWMD. Regarding springs, the agencies
include the SRWMD (plus its subcontractor), the SJRWMD, the SWFWMD, and the USGS. For
wells, samples were collected by the NWFWMD, the SRWMD and its subcontractor, the

BULLETIN NO. 69

SJRWMD, the SWFWMD, the SFWMD, and the FDEP. In addition, multiple analytical
laboratories were used to process the samples.

For the 1991-2003 time sequence, spring sampling and analyses faced all of the potential
aforementioned problems. During the same time period, especially during the early days of the
operation of the TV Network, well monitoring encountered many of the same problems that
spring monitoring encountered. The TV Network is operated by the FDEP and by the mid
1990s, the FDEP reduced a considerable portion of unwanted variability by adopting a policy of
using a standardized sampling protocol, a standardized method of sample transport, a single
analytical laboratory, and a standard set of analytical methods and reporting protocols. It is
hoped that one day, spring monitoring throughout Florida will also adopt similar protocols that
will reduce variability.

In spite of the potential variability, not all is negative. For all water samples and data used
in this report, each corresponding sampling agency and/or analytical laboratory has an
individually-approved quality assurance/quality control (QA/QC) plan on file with FDEP.
Regarding QA/QC, the contact for each WMD, FDEP, and the USGS are found in Appendix G.

It should be noted that by 2001, in an effort to achieve standardization, the FDEP adopted
a recommended method for spring-water quality sampling. An overview of the protocols is
found in Scott et al. (2004). The TV Network is managed by the Watershed Monitoring Section
(WMS) of the FDEP. It recently produced an overview of its well water sampling protocols
(Florida Department of Environmental Protection, 2003).

Analytes used in this study

Multiple agencies collected water-quality samples for this publication; however one
agency may have sampled one analyte, while another agency sampled a similar analyte that was
closely related to the first. This was quite common for the analytes nitrate, ammonia, phosphate,
phosphorus, magnesium, sodium, potassium and chloride. Most often, the difference was
between the collection of the dissolved (filtered sample) and total (unfiltered sample) form of the
analyte. It would be preferable if sufficient data in both the dissolved and total forms of these
analytes were available. Unfortunately, it was not always the case. It was decided to combine
the total and dissolved forms because of the importance placed on nutrients in order to obtain a
time series with a sufficient number of data values. We do not recommend this procedure in the
future because it would be better to use one or both of the forms in conducting statistical
analyses. In the recommendations section (discussed later) we recommend a more consistent set
of analytes be used in the future. Nevertheless, for this study, we occasionally used a combined
surrogate form of nitrate, ammonia, phosphate, phosphorus, magnesium, sodium, potassium and
chloride. We did this solely for the purpose of obtaining a sufficient amount of data necessary
for data analyses.

Grouping of Analytes

For convenience, and in an effort to better understand groundwater quality trends, the
analytes (or indicators) were divided into several groups. They are: (1) Field, (2) Rock-matrix

FLORIDA GEOLOGICAL SURVEY

or Rock, (3) Saline or Saltwater, (4) Nutrient, and (5) Other analytes. However, because of
occasional chemical complexities, many analytes are grouped into more than one category.
Table 5 lists them by group. Note that analytes in the table only refer to those that displayed
trends. A detailed description of each analyte is found in Appendix F.

Each analyte represents a measure or variable that can be used to assist in judging the
overall health of Florida's groundwater. Field analytes such as discharge, water level, and flow
describe quantity, but they can also greatly affect quality. The rock analytes suggest upcoming of
water from deep within Florida's aquifers. The saline analytes suggest intrusion or upcoming of
water from the deep portions of our aquifers, and the nutrient analytes are those that stimulate
biological growth or are present as a direct result of biological activity.

Field Analytes

Field analytes represent a grouping for convenience. Measurements of field analytes
were conducted prior to collecting samples for laboratory analyses. The analytes in this group
that were used for trend analyses include: discharge (or flow), dissolved oxygen (DO), pH,
specific conductance (SC), water temperature (Temp), and water level [water level relative to
mean sea level (msl) based on the North American Vertical Datum (NGVD) of 1988)].

Rock-Matrix Analytes

Rock-matrix analytes are those indicative of the rocks making up an aquifer. Because of
natural rock weathering, water that has had a long residence time in an aquifer system has a

OI ,

BULLETIN NO. 69

greater probability of having a high concentration of dissolved rock matrix material. Rock
indicators include: alkalinity (Alk), calcium (Ca), magnesium (Mg), plus to a lesser extent,
fluoride (F), iron (Fe), pH, potassium (K), strontium (Sr), sulfate (SO4), phosphorous (P),
orthophosphate (P04) and SC. Since phosphate and phosphorus are often found in the mineral
fluorapatite, these two analytes are also included in the rock-matrix group.

Saline or Saltwater Analytes

Saline analytes are those associated with salts within either connate water or seawater.
Connate waters are those waters trapped within the sediments at the time of their deposition.
Since the original sediments were deposited in a marine environment, the pore spaces contain
very old saltwater. Saline analytes are obviously also found in the seawater located along
Florida's coasts. The major difference is the age of water. High concentrations of saline
analytes are often an indication of horizontal saltwater encroachment. However, they can also be
an indication of encroachment of highly mineralized water from the deeper portion of Florida's
aquifers, below the fresh-water "lens". The encroachment can be caused by the depletion of the
less dense fresh-water "lens" during a very dry period (e.g. a drought), or by the upcoming of
connate water during periods of heavy groundwater withdrawals. Pumping of groundwater
increased during dry periods and this process exacerbated the apparent intrusion process. Saline
analytes include: calcium, chloride, potassium, sodium (Na), specific conductance, sulfate, total
dissolved solids (TDS), plus water level (MSL) and stage.

Nutrient Analytes

Nutrients represent naturally occurring compounds or elements that are essential for the
growth of living organisms. However, if found in high concentrations, over-enrichment of
nutrients eutrophicationn) in a body of surface water can lead to an overgrowth of plant life
(including algae) and possibly a loss of dissolved oxygen. For this report, nutrient analytes
include: organic carbon, phosphate, phosphorus, a series of nitrogen related species, and to a
lesser extent, Mg, Ca, K, and sulfur in the form of sulfate. The nitrogen related species include
nitrogen, ammonia, total kjeldahl nitrogen, nitrate, and nitrite.

Other Analytes

Analytes in the "other" category do not fit in any of the other four categories. They
represent a miscellaneous group. For trend analyses, the analytes included in this group are
suspended solids, and turbidity.

DATA

The original data were from several sources. The data used for the trends analyses
discussed in this document are in Appendix H.

FLORIDA GEOLOGICAL SURVEY

Data Sources

The majority of the water-quality data from the springs were collected and analyzed by
the water management districts. The data for wells were obtained from the FDEP Watershed
Monitoring Section.

Data Verification

The analysis of the data was verified several times with processes including internal and
external reviews in addition to repeat analyses by each author. The internal review consisted of
audits performed by two of the authors (N. Doran and A. White). These audits included hand-
eye verification of every analysis figure for accuracy. Repeat calculations were performed and
compared with the first value made using new values calculated from the original data. When
errors were found, the data were recalculated by at least two of the co-authors and then replaced.

The external verification was conducted through multiple meetings with WMD staff.
During these meetings many of the actual samplers and initial compilers of the data were present.
Two rounds of discussion took place; once before this document was compiled and again as it
neared completion. These meetings lasted for several hours and many comments were made on
procedures and verification policies. Each concern was subsequently addressed and is exhibited
in the subsequent sections of this document.

Data Preparation

Preparing the data for analysis included addressing the problems of seasonality, missing
values, duplicate data, censored data and detection limits. The data variation caused by seasonal
cycles increases the difficulty of detecting long-term trends. This problem can be alleviated by
removing the cycles before applying tests or by using tests unaffected by the cycles (Gilbert,
1987).

Missing values (i.e., samples that were never collected) cause their own special
difficulties for analysis. For example, suppose 12 monthly water samples were scheduled to be
collected from a selected well in a given year. Suppose that for a variety of reasons, only 10
were actually collected. Thus, the well had two missing values for each indicator sampled.
Unless otherwise stated for the statistical analyses, missing values were treated as if they were
never collected. For example, if only 10 samples were collected, then descriptive statistics were
based on 10, instead of 12 samples.

Duplicate data resulted from two samples collected from the same spring or well
consecutively. The two samples were then labeled as representing two different sampling
events and sent to a laboratory for analyses for the same set of analytes. The purpose of
duplicates is to evaluate the internal precision of a laboratory. For statistical analyses, it was
decided that the primary sample, collected first in the time sequence, would be used. The second
duplicate sample was only used for quality assurance evaluations.

BULLETIN NO. 69

The minimum detection level for analytes from analytical laboratories can cause
environmental data to be censored. That is, the distributions are truncated at their lower ends
near the laboratory detection level. As stated earlier, for statistical analyses, all data reported as
"Below Detection Level (BDL)" were arbitrarily set at the detection level. In addition, it should
be noted that for a given analyte, over the period of record, the laboratory detection levels
changed, giving multiple detection limits.

Time Sequences

Data for analyses were segmented into three time sequences: Sequence A (1991-2003),
Sequence B (1991-1997), and Sequence C (1998-2003). The first sequence spanned the entire
sampling period, January 1, 1991 to December 31, 2003. The two smaller time sequences were
used to assist in identifying and evaluating shorter-term trends (five to six years).

Within the time sequences, each analyte needed to have a minimum of 10 data points in
order for any statistics to be performed. In addition to the minimum number of 10 data points, it
was arbitrarily decided that for Sequence A at least three data points from Sequence B and at
least three data points from Sequence C needed to be present. If Sequence A lacked this
additional criterion, then no analyses were performed on the sequence. As an example, suppose
a spring had 15 data points, 12 in Sequence C and three in Sequence B. An analysis for trend
was conducted for Sequence A, and C, but not B. If a spring only has 14 data points, 12 in
Segment C and two in Segment B, then no analyses was performed for Sequence A nor
Sequence B. However, the statistical analysis was conducted for Sequence C. A question
arises, are only three data points sufficient to represent the time Sequence B or C within
Sequence A? It certainly is not desirable and is an example of "messy" data. This situation was
considered to be sufficient for trend analyses because this study represented the first statewide
analyses for trends. Fortunately, this was not a common situation and, hopefully in the future,
available data will be less "messy."

Data Used for Analyses and Explanation of Appendices

All data presented in this report represent a collaborative effort among the five water
management districts, the U.S. Geological Survey and the Florida Geological Survey for spring
data, plus Alachua, Palm Beach, Broward, Miami-Dade, Lee, and Collier Counties for well data.
This is significant since each sampling agency has its own agenda resulting in different reasons
for the collection of a particular analyte.

Resultant data for both springs and wells can be found in Appendix H. The appendix
contains the actual concentrations for the analytes measured. The state is broken down into three
regions, Northwest, Central, and South Florida. Within each regional folder, the data are placed
in their respective WMD. Missing data were noted with an asterisk. In the folder, the results of
the MK analyses along with the corresponding n (number of data points) and the Sen Slope (SS)
for each spring and well (to be discussed later) can also be found. The format is similar to that
within the data folder. Finally, plus/minus charts (to be discussed later) are also included.

FLORIDA GEOLOGICAL SURVEY

The data in the statistical analysis folder are temporal data. A numerical value of -9999
was included to maintain the order of the spread sheet. A value of -9999 can either mean that
data are missing or it can mean that there are an insufficient number of samples to perform the
statistical analyses (procedures to be discussed later).

The remaining data were placed in tables. The tables contain the following information:
(1) the identification (ID) that names the spring (or well), (2) its location in latitude and
longitude, (3) the time sequence, (4) the dates for which samples were obtained, (5) a p-value for
significant increase, (6) a p-value for significant decrease, (6) the total number of samples within
the sequence, (7) the calculated SSs, and (8) the trend results. With regards to the results, the
tables indicate whether there was a significant increase (UP), decrease (DOWN), or no evidence
of trend. Throughout this report an upward trend will be designated with either an up arrow (1)
or a plus sign (+). A downward trend will either be designated with a down arrow () or a
negative sign (-).

INFORMATION GOALS AND DATA ANALYSIS PROTOCOLS

Information Introduction

The purpose of data analyses was to document water-quality trends in Florida's springs
and wells for the period 1991 2003. Prior to evaluation, a list of information goals was
developed. The goals were then turned into specific questions for which statistical procedures
could be used in an attempt to answer them. The questions are listed below and are followed by a
discussion of the statistical procedures used in this report. A more detailed discussion of all
statistical procedures used in this report can be found in Appendix E. 1 and E2. Minitab Release
14 (Minitab, 2003) and S-PLUS 6.2 Professional Edition (S-PLUS, 2003) were used for all
analyses. The six questions were:

1. What were the statistical distributions for each of the sampled analytes?
2. For Sequence A (the longest time sequence), for each analyte, and for each
spring or well, was seasonality present?
3. For each sequence, for each analyte, and for each spring or well, were
linear time series trends present?
4. If trends were present, what were their slopes?
5. For springs or wells with detectable trends, were they spatially related?
6. If evidence was found to indicate that the degrading trends were man-induced,
what are plausible solutions and recommendations?

Overview of Statistical Analyses Procedures

Descriptive Statistics

Descriptive statistics were produced for each analyte at each spring and well (station) for
the longest time sequence. The descriptions can be found in Appendix I. For each sampled
station for Sequence A, the tables list the analyte (or indicator), the measurement unit, the

BULLETIN NO. 69

number of samples collected, the number of samples with concentrations below the laboratory
detection level (BDL), the minimum value, the first, second and third quartiles, and the
maximum value. The first, second and third quartiles (Q1, Q2, and Q3) correspond to the 25th
50th (median), and 75th percentile respectively. An example of the descriptive statistics is
presented in Table 6. For a given analyte, the reported minimum concentration value in the table
often reflected the minimum detection level reported by the analytical laboratory.

Seasonality can be thought of as periodic fluctuations or cycles. As an example, Figure
11 displays monthly water temperatures for an imaginary well during the 1992 calendar year.
Not surprisingly the temperature is highest during the summer and lowest during the winter
months, indicating that for temperature there exists a one year cycle.

Figure 11. Monthly water temperatures plotted over the 1992 calendar
year for an imaginary well.

Cycles are not restricted to calendar years. They can occur over virtually any length of
time. Figure 12 displays an example of a cycle longer than one year. In the example, the
concentration of an imaginary analyte has a six year cycle or season. Depending on the variable
of interest, it may or may not have been influenced by cycles whose frequencies are longer than
13 years; Sequence A was 13 years in length (1991-2003). It is difficult to make that

determination of the cycle's influence on the analyte. With this in mind, the authors were
concerned with the influence of shorter term cycles on Sequence A. Since ground-water samples
were collected on a quarterly and monthly basis while springs were sampled either on a quarterly
or quasi-quarterly fashion, it was decided to determine if cycles in those frequencies were
present in the data.

6

"-" 2
0

S-2 -

o -4 -
-6 -11
0 5 10 15 20 25
T im e (y ears)

Figure 12. Example illustration of seasonality with a six-year cycle.

For each spring or well for Sequence A, the presence of seasonality for each sampled
analyte was determined using a Kruskal-Wallis (KW) test (Hollander and Wolfe, 1973; Gilbert,
1987). Quarterly and monthly seasonality tests were conducted because stations were generally
sampled quarterly and occasionally monthly. It should be noted that monthly seasonality tests
could only be conducted if samples were collected on a monthly or quasi-monthly basis. For the
most part, monthly samples were only collected for 24 of the 46 wells and only for field analytes.
On the other hand, quarterly samples were obtained on the remaining wells and quasi-quarterly
samples were collected on most of the springs. The quasi-quarterly sampling by the WMDs and
the arbitrary seasonal breakdown was as follows: (1) December February, (2) March May, (3)
June August, and (4) September November. It should be noted that as we conducted the
analyses for trends, we found that, based on the four arbitrary seasons, most analytes did not
display significant seasonality. We recognize that in the future, with the acquisition of additional
data and with additional trend analyses, a better breakdown may be discovered. Nevertheless,
for this analysis exercise, the KW test was used to compare the distribution of two or more
populations (seasons) by indirectly comparing their median values during each season as defined
by this study. If we had defined only two seasons, the KW test is equivalent to a Mann-Whitney
(MW) test (Conover, 1999). Both tests are discussed in greater detail in Appendix E. It should
also be noted that the results of the MW test are identical to another very similar test; the
Wilcoxon rank sum test (WT) (Conover, 1999). The WT test was occasionally used during this

BULLETIN NO. 69

study because some of the statistical software used included the WT test rather than the MW test.
Conover (1999) discusses the WT test in detail. Results of the WT test are identical with those of
the MW test.

Consider a situation in which one wants to determine if two populations have the same
statistical distributions for a given season and samples are therefore obtained for each season.
For the MW test, the null hypothesis is that the median of the two populations are the same while
the alternate hypothesis is that they are not. The two samples are combined into a single ordered
sample from smallest to highest. Each observation is then assigned a rank without regard to
which sample it originally came from. The sum of the ranks assigned to those values from one
of the populations is then generated. If the rank sum of the corresponding population is very
small (or very large), there is an indication that the values from one population tends to be
smaller (or larger) than the values from the other. If so, the distributions of the two populations
are not equal. If the rank sums of the two populations are not equal, neither are their medians.

Returning to the KW test, it compares the distribution of more than two populations (e.g.,
seasons). For this report, each test was two-sided. The null hypothesis is that the median
concentration of an analyte sampled in any season is equal to the median of the remaining
seasons. The alternate hypothesis is that the median concentration for at least one season is not
equal to the others. Under the latter scenario, it is assumed that seasonality does exist. For
quarterly data, tests were conducted assuming that each quarter was a season. For monthly data
sets, tests were conducted assuming that each month was a season. The level of significance was
preset to a = 0.05.

For example, 38 temperature samples were collected at Weeki Wachee Main Spring for
time Sequence A. However, data were not available for the period 1991 through most of 1993.
Data were available for the 1993-2001 time frame. All samples were sampled on a quarterly
basis; nine in each of seasons (1), (2), and (4), plus ten in season (3). The KW test compared the
median values for each of the four seasons and, based on the test, it was concluded that the
median of at least one season did not equal the other medians. Thus, it was concluded that
quarterly seasonality does exist for the spring with respect to temperature. Since monthly data
were not available, no conclusion could be made regarding monthly seasonality. Results for
these analyses are found in Appendix J.

Deseasonalized Data

If seasonal cycles were present in the data, the data were deseasonalized using a method
presented by Intelligent Decision Technologies (1998). Although most measurements of central
tendency used in this report pertain to the medians, means were used (Sen, 1968) in the
deseasonalization transformation equation (Intelligent Decisions Technologies, 1998). The Sen
method subtracts the mean of the corresponding season from each datum and then adds the
overall average (mean) of the sequence back to the original datum. For example, suppose 10
years of quarterly data were collected at a site for chloride. Suppose the overall mean of the data
for the 10 year period was 1.0 unit while the mean of the winter quarter was 0.2 mg/L. Now
suppose a concentration for a particular winter quarter sample was 1.2 mg/L. In mg/L, the
corresponding transformed, deseasonalized datum becomes:

Gilbert (1987) stated that the Mann-Kendall (MK) test can be viewed as a nonparametric
test for zero slope of the linear regression of time-ordered data versus time. Given that it is a
nonparametric technique, it does not depend on an assumption of a particular underlying
distribution. The test identifies correlations in data through temporally ranking the data and then
determining the number of times the concentration goes up or down relative to the previous time
step. It only uses the relative magnitudes of the data rather than their measured values.

Data reported as trace or below the minimum detection level (MDL) were used by
assigning a common value that was smaller than, or equal to, the smallest measured value in the
data set. For this report, below detection level (BDL), was assigned an arbitrary value equal to
the detection level (DL).

Once the seasonality tests were completed (results found in Appendix J), each analyte
was tested for a linear trend using the MK test (a = 0.05) for each time sequence. A macro
program was used for the analysis while working within Minitab [Appendix E. 1)]. However, if
data were insufficient (n < 10), the MK test was not conducted. For this exercise, we always
used a one-sided test. The reason was that we had a preconceived idea as to whether or not a
downward (or upward) trend was an indication that conditions were getting worse (or better).
The results of the MK tests are found in Appendix K.

Seasonal Kendall Test

A common test used in the analyses of time series is the Seasonal Kendall (SK) test
(Gilbert, 1987). It is an adoption of the MK test, and can be used if there is seasonality in the
data. The SK test is the technique of choice. Unfortunately, it has a set of requirements that
were not obtainable. Miller et al. (2004) mentioned that the test requires that the percentage of
censored data (e.g. data reported as BDL) be no more than about five percent. In addition,
Miller stated that there should only be one censoring level. This latter requirement was not
obtainable because our data were obtained from agencies operating independently of each other.
The agencies used multiple laboratories with multiple detection levels, which amounted to
multiple censoring levels. Thus, the SK test was not used in this investigation. In the future, as
better and more consistent data are obtained, the SK test is the recommended test.

Sen Slope

If a trend was found to exist for either non-seasonal or seasonal data, its corresponding
slope was determined using a Sen Slope (SS) estimator (Sen, 1968; and Gilbert, 1987). The
estimator measured the median difference between successive concentration observations over
the time series. The SS was used only to measure the magnitude of the slope. It was not used as
a hypothesis test. Results are found in Appendix K.

BULLETIN NO. 69

Sign Test

For each analyte exhibiting a trend, a map showing the location of the corresponding
station was created. In addition to statistical evaluations, visual estimates were made as to
whether clusters of corresponding upward or downward trends existed. Associations with depth,
land use, and other relationships were evaluated. The last statistical procedure used was the sign
test (Sullivan, 2004). The sign test is a relatively simple procedure to conduct. It was used to
determine if a significant number of stations demonstrated upward or downward trends over a
geographical region. Note that one spring in the SWFWMD was not used in the analyses. The
reason will be discussed later.

As an example, suppose during Sequence A, 29 of the 57 springs displayed an upward
trend for nitrate. Can it be concluded that there exists an upward statewide trend? What if 40 (or
45) of the springs demonstrated upward trends? If one thinks of the causes of trends in
individual stations as being random processes, we could expect about half of the springs to have
upward trends, while about half should have downward trends. On the other hand, if a large
proportion of the springs had upward trends, we might be suspicious that one or more
phenomena were affecting springs and causing the upward trends over a region. Finally, if an
extremely large proportion of the springs demonstrated upward trends, we would become even
more confident that the phenomena were affecting the upward concentrations over a region.

For the sign test, one assigns a (+) value if there is an upward trend and a (-) value if
there is a downward trend. Sullivan (2004) stated that zeros add nothing to the test and therefore
should be eliminated from further analysis. Thus, all springs demonstrating no trend were
assigned a value of zero (0) and were eliminated from further analyses. The test simply
compares the proportion of + values to the values. For this exercise, a was preset to 0.05 for
the level of significance for these evaluations.

Caveats and Assumptions

It should be noted that this study was not set up as a designed experiment. We took
existing data and attempted to evaluate them. As a consequence, there were many less-than-
perfect situations that we needed to address in order to conduct the statistical analyses related to
this project. Whenever one takes existing data which were originally collected with a variety of
goals in mind and attempts to evaluate them with a new set of objectives, problems should be
expected. For example, R.A Fisher, a statistician sometimes referred to as the "Father of
Modern Sitaisi \" (Sullivan, 2004), once stated, "To call in the statistician after the experiment
is done may be no more than asking him to perform a postmortem examination: he may be able
to say what the experiment died of This quote is appropriate for our study. We faced many
unpleasant situations with regard to the data analyses.

One of the major sources of problems pertained to the assumptions of the statistical
procedures (see Appendix E). Generally these tests assumptions are: (1) the measurements are
mutually independent, (2) the observations are random, (3) the populations are continuous, and
(4) the scales or measurements are at least ordinal. For the sign test, the assumptions are slightly

FLORIDA GEOLOGICAL SURVEY

different: (1) the stations are mutually independent, (2) the measurement scale is at least ordinal,
and (3) if the probable outcome of a sign is (+) or (-), for one station, the same is true for all
other stations. With the exception of the independence issue, the assumptions were valid. The
issue of dependency will be addressed during the discussion of the results of the study.

RESULTS

The trend results of every spring and well for each analyte can be found in Appendix K.
What follows is a set of examples from selected springs and wells. Our purpose is to give the
reader a generalized idea about the behavior of analytes during the study period. Although some
discussion regarding the causes of trends at an individual spring will be discussed, the emphasis
of this report is on regional and statewide trends. A discussion regarding the possible sources of
the analytes and the most probably causes of trends can be found in Upchurch (1992) and
Appendix B2. The trend results are divided into both springs and wells by water management
district. There were no springs analyzed in the SFWMD. Thus springs were geographically
divided into the NWFWMD, SRWMD, SJRWMD, and SWFWMD. A note is needed regarding
the relationship between time-series figures and Sequences. If sufficient data were available,
time series analyses were generated for each Sequences A, B, and C. However, if data were
missing for the front or back end of the Sequence, the corresponding figures still cover the entire
sequence. As an example, the first series discussed is for magnesium in Wakulla Spring during
Sequence A (1991-2003). Unfortunately, no data exists for the last two years of the sequence.
Nevertheless, the figure displays the entire sequence. This is true for all time series discussed.

Springs

Northwest Florida Water Management District

In the NWFWMD, only Wakulla Spring (Figure 13) had sufficient data for analyses for
this study. Wakulla was sampled through a piece of tubing placed into a major conduit of the
spring. Thus, the samples are considered spring-water samples. However, for years, the FDEP
has, for administrative purposes, considered the tubing to be a well (Well 67 in the Temporal
Variability Network). Since FDEP considers the station to be a well and the fact that the tubing
taps a spring vent, the station for this report was analyzed both as a spring and a well. Stage data
were collected at the spring vent, and stage was used in lieu of water levels.

Rock and Saline Analytes, Nutrients, and Flow

Rock-matrix analytes included cations such as calcium and magnesium. Wakulla Spring
shows an increase in dissolved magnesium over time Sequence A (1991-2003). Increases in
magnesium and specific conductance (SC) are illustrated in Figure 14. The time series for
magnesium at Wakulla, like many analytes, showed inconsistent sampling over the period of
record. In this case the time period from 1994 to 2000 contained only one point. For the
given data, the MK

BULLETIN NO. 69

= ..-.
L n

Legend

Sakulla

Springs .
NWFWMD
SRWMD

Miles N
10 20 40 60
Kilometers W* E
15 30 60 90 S

Figure 13. Location of Wakulla Spring within the NWFWMD.

test confirmed an increasing trend (p < 0.05). For almost every time-series figure, the median
value of the second half of the sequence was compared to median of the first half, using the
Wilcoxon rank sum test (WT). This enabled us to not only determine the slope of the trend, but
to also better evaluate magnitude of change during the time series. There was a significant
change over the period of record (p < 0.05). Whether by analysis of trends, or comparison of two
halves of the time sequence, the latter half of the study revealed elevated values of dissolved
magnesium. The missing data from the intervening years in the magnesium time series (Figure
14, top) appear to be accounted for in the time series for SC (Figure 14, bottom). Wakulla Spring
showed a clear increase in SC over time. The probable causes for the increases in magnesium
and SC, will be discussed later on a districtwide and statewide perspective.

Figure 15 (top) displays a trend for nitrate-nitrite concentrations in Wakulla Spring for
the 1991-2003 time frame. The time series shows noticeable data gaps from 1995 to 2000 and
again during 2001-2003. In the Wakulla Basin, Chelette et al. (2002) indicated that there are
several significant sources of nutrients. These include effluent from a large spray field, fertilizer
application, and numerous onsite waste disposal treatment sites (OSTDS) within the basin, and
up-gradient of the spring. Fortunately, it appears, since 1991, the concentration of nitrate has
significantly decreased. Nitrate in the form of dissolved nitrate-nitrite declined (Figure 15, top).

FLORIDA GEOLOGICAL SURVEY

Wakulla Spring Time Sequence A (1991-2003)

a^^m ^
^--^^^ a

10.5

10.0-

E 9.5 -

S9.0

8,5

8.0

7,5

MK p-value=0.0002 na= 15 nc= 6
WTp-value=0.0112 SS= 0.0750

Wakulla Spring Time Sequence A (1991-2003)

* .

a
a,

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Date
MK p-value <0.0001 nB = 52 nc=53
WT p-value <0.0001 SS =0.52587

Figure 14. Increasing rock analytes at Wakulla Spring. Magnesium
(top) and specific conductance (SC) (bottom) have upward trends
(p < 0.05). Tests include MK for time series trends, (WT) on sequences
B and C (first and second half of study), plus SS calculations on the
rates of changes.

Figure 15. Decreasing nitrates and water levels at Wakulla Spring.
Dissolved nitrate (top) and water levels (bottom) had significant trends.
Tests (p = 0.05) included MK and WT. WT compare medians of the
first and second halves of the study. (1.0 m = 3.3 ft)

N U

U
U
U U

U U
U I
C

Y
U

U
U

U

FLORIDA GEOLOGICAL SURVEY

MK and WT tests indicate that whether by trend analysis or comparison of the first and second
half of the time sequences, concentrations of nitrogen decreased. Loper et al. (2005) suggested
that the decreasing nitrate concentrations were due to lowered concentrations of effluent from a
large spray field located within 16 km (10 mi) of the spring. Figure 15 (bottom) illustrates a
significant drop in stage level.

Suwannee River Water Management District

Figure 16 displays the locations of the 15 springs located in the Suwannee River Water
Management District (SRWMD) used in this report. The spring names and the abbreviations are
found in Table 7.

Many of the springs are located along the Suwannee River, along a section of the river
which is roughly perpendicular to the coast, at least in its lower stretch. Numerous trends were
noted along an approximate south to north, or lower to upper, river direction. (Specific results are
found in Appendix K).

Rock-Matrix and Saline Analytes

Calcium, magnesium, and sodium increased strongly in the SRWMD over Sequence A.
Increases were particularly strong in the latter half of the study (Sequence C). Increasing trends
were dominant for several analytes. Magnesium and sodium had significant increases in eight of
14 springs with no decreases. Calcium increased in nine springs. Examples of increases in the
rock indicators are shown in Figures 17-20. Figures 17 and 18 illustrate trends in calcium for
four springs over Sequence A while Figures 19 and 20 demonstrate patterns for magnesium for
four springs over Sequence A or C, depending on the spring.

Note that for many of the time-series figures that compared two stations, the vertical
scales do not coincide. By keeping the vertical scales constant, occasionally the variability of
one graph became so small that you could not see it. In the end, we decided it was better to use
inconsistent vertical and to emphasize variability over time.

Changes in calcium in springs for the lower Suwannee River are similar to changes in
springs farther north. Fanning Spring (FAN) and Gilchrist Blue Spring (GIL Blue) illustrate two
of the nine springs that exhibited an increase in calcium (Figure 17). In addition to calcium,
FAN showed significant increases in other rock-matrix and saline indicators including alkalinity,
chloride, potassium, magnesium, sodium, and specific conductance. The time series plot in
Figure 17 shows a gradual increase in calcium from 60 mg/L in 1995 to approximately 80 mg/L
in 2003; the gradual increase had a low variance around the best fit line. When data for
sequences B and C were compared, Sequence C data had clearly higher medians (WT test p-
value, <0.0001, illustrated by box plots in inset figure in bottom corner). Like FAN, for
Sequence A, calcium concentrations in GIL Blue increased. The initial concentration was about
50 mg/L and ended with 65 mg/L; both springs increased in concentration by approximately 20
mg/L. GIL Blue also had many other analytes with upward trends that mirrored FAN: alkalinity,
chloride, magnesium, sodium, and specific conductance. Springs farther north (Figure 18) had
similar looking trends to those springs located farther south (Figure 17), although the overall
trends in other analytes were different. Suwannee Blue Spring (SBL) and Troy Spring (TRY)
together had increases in only

FLORIDA GEOLOGICAL SURVEY

Fanning Springs Time Sequence A (1991-2003)

M.N Mi
- ,,,.,,

-a

0
S40-

20 -

0 -
1/1/1995

5/22/1997

10/11/1999
Date

3/1/2002

MK p-value =0.0005 nA= 10 nB= 40
WT p-value <0.0001 SS =0.2694

Gilchrist Blue Spring Time Sequence A (1991-2003)

*.

1993 1994 1995
MK p-value =0.0005
WT p-value =0.0563

1996 1997 1998 1999 2000 2001 2002
SS =0.2694 Date
nIA 8 nB= 33

Figure 17. Increasing rock analytes at Fanning and Gilchrist Blue
Springs. Fanning (top) and Gilchrist Blue Springs (bottom) had
significant increases in calcium. Tests (p < 0.05) included MK for
for trend, WT on Sequences B and C, plus SS calculations on the rate
of change. Beginning and ending sampling dates for the two springs
are not the same.

Figure 18. Increasing rock analytes at Suwannee Blue and Troy Springs.
Suwannee Blue (top) and Troy Spring (bottom) had significant increases in
calcium. Tests (p < 0.05) included MK for trend, WT on Sequences B and C,
plus SS calculations on the rate of change. Beginning and ending sampling
dates for the two springs are not the same.

12/16/2003

* *~ .*

t .

11/8/1992
MK p-value
WT p-value

FLORIDA GEOLOGICAL SURVEY

Manatee Spring Time Sequence A (1991-2003)

10/1/1997

2/2/2000

6/5/2002

MK p-value <0.0001 SS 0.0351 Date
WT p-value <0.0001 ni = 22 n2 = 22

Hart Springs Time Sequence C (1998-2003)

35 1
5/1/1996
MK p-value
WT p-value

4/12/1998 3/24/2000
=0.0017 SS 0.066667 Date
=0.006 ni = 9 12 = 9

3/5/2002

Figure 19. Increasing rock analytes at Manatee and Hart Springs.
Manatee (top) and Hart Springs (bottom) had significant increases in
magnesium. Tests (p < 0.05) included MK for trend, WT on the first (1)
half and the second (2) half of both time series. Beginning and ending
sampling date for springs are not the same.

Figure 20. Increasing rock analytes at Poe and Lafayette Blue Springs.
Poe (top) and Lafayette Blue Spring (bottom) had significant increases in
magnesium. Tests (p < 0.05) included MK for trend, WT on the first and
second half of both series, and SS calculation on rate of change. Beginning
and ending sampling dates for the springs are not the same.

Toward the south, Manatee (MAN) and Hart (HAR) (Figure 19) began the time series
with approximately four mg/L of magnesium; by the conclusion of the series, they were at six to
seven mg/L. Further north, Poe Spring (Poe) (Figure 20) began at about four mg/L in 1998 and
rose to about 10 mg/L in late 2002. Lafayette Blue Springs (LBS) (Figure 20)( began at about
eight mg/L in 1998 and rose to about 14 mg/L in 2001.

Flow

The SRWMD consistently collected flow or discharge data at specific spring vents during
the same day that they collected water samples from their springs. However, the SRWMD did
not begin collecting discharge data until the 1997-1998 time frame.

During Sequence C, for the SRWMD, flow rates decreased significantly in 12 of 16
springs. There was not an increase in flow rate in any of the springs during the same time
sequence. In addition, the degree of decrease in flow was sometimes severe. Figures 21-24
illustrate the trends for eight springs starting at the lower end of the Suwannee River and moving
inland and northward.

Springs at the lowest end of the Suwannee River included Fanning (FAN) and Hart
(HAR) Springs (Figure 21). Both springs show substantial drops in flow levels. By the end of the
period of record, flow was reduced to approximately half the levels seen at the beginning of the
time series. FAN's highest recorded flows were near 120 cubic feet per second (cfs), but ended
near 50 cfs. HAR's highest recorded flow was approximately 90 cfs and fell to near 40 cfs at the
end fo the time series.

Upstream from these springs are Rock Bluff (RKB) on the Suwannee and Hornsby
(HOR) Springs on the Santa Fe River (Figure 22). Both displayed even sharper declines in flow.
Rock Bluff went from a high of 50 cfs to under 20; flow was reduced to zero cfs briefly in 2001.
Hornsby showed an even stronger decline: over 200 cfs was measured in 1998 and the flow
reduced to zero cfs during a period starting in early 2000. This was followed by a small recovery
of flow rate in 2003.

Poe Spring, on the Santa Fe River, and Little River Sulfur Spring (LRS) on the middle
Suwannee region had strong declines in flow rate (Figure 23 (Sequence A; but mostly C)). Poe
Spring recorded discharges of 60 to 80 cfs near the beginning of the time series but declined to
near 20 cfs by the end. LRS began the time series with a flow rate near 90 cfs and ended near
20. Decline in flow at LRS closely followed a regression line fit to the date (Figure 23, bottom).

Troy (TRY) and Telford (TEL) Springs both had downward trends in flow. Though flow
at Troy was approximately three times higher than Telford (Figure 24; Sequence A, but mostly
C)), there was a slight increase in flow in mid-1998 followed by a decrease for both springs in
early 2000, and then another slight increase in flow occurred in late 2001. Overall, both springs
seem to show that flow was reduced by at least half, with LRS indicating a reduction in flow by a
third at the end of the time series.

Figure 21. Decreasing flow at Fanning and Hart Springs. Between 1998
and 2001 Fanning (top) and Hart Springs (bottom) had significant de-
creases in flow. Tests (p < 0.05) included MK for trend, WT, plus an
SS calculation on rate of change. Over the period of record, flow at both
springs was reduced significantly. Beginning and ending sampling dates are
not the same. [One cfs equals 0.028 cubic meters per second (cms).]

Figure 23. Decreasing flow at Poe and Little River Springs. Poe (top)
and Little River Springs (bottom) had significant decreases in flow. Tests
(p < 0.05) included MK for trend, WT, plus an SS calculation on rate of
change. For both Poe and Little River flow reduced to about one third by
the end of the series. Beginning and ending sampling dates are not the same.
(One cfs = 0.028 cms)

Figure 24. Decreasing flow at Troy and Telford Springs. Troy (top) and
Telford Springs (bottom) had significant decreases in flow. Tests (p < 0.05)
included MK for trend, WT, plus an SS calculation on rate of change. Over
the period of record, flow at both Troy and Telford was reduced by half. Be-
ginning and ending sampling dates are not the same. (One cfs = 0.028 cms)

6/1/2003

- .

10 -
1/1/1997

5/1/2003

BULLETIN NO. 69

Nutrient Analytes

For the study period, nutrients in the SRWMD had more complex patterns than the
patterns of either the salinity indicators or flow. While some nutrient trends were very strong,
others were not as clear. During Sequence A, o f the 15 springs in the SRWMD, TKN increased
significantly in nine springs (with no decreasing trends). Nitrate appeared to decrease (downward
trend in six springs, while it increased in three springs). At the same time, other nutrients-
phosphorus and phosphate specifically-appeared to increase. For phosphorus, there were five
springs with increasing trends and only one spring indicating a decrease; for phosphate there
were four springs with increasing trends and only one spring with a decreasing trend.

The FDEP has a maximum nitrate standard of 10 mg/L for groundwater and Class I
surface water before considering the water impaired. Both water standards are directed toward
maintaining drinking water quality (Florida Department of Environmental Protection, 1994).
Currently, there is not a numeric standard that is directed toward changes and concentrations of
biota in surface water. However, FDEP has established a non-legal threshold for nitrate and
phosphorus for surface water (Florida Department of Environmental Protection, 2004). The
thresholds were based on a statewide evaluation of chlorophyll concentrations in lakes. The
groundwater-surface water relational assessment (SRA) limit is 0.45 mg/L for nitrate.
Groundwater nitrate concentrations exceeding the 0.45 mg/L limit suggest that there is a
potential for adverse affects on aquatic organisms in the spring runs. Technically, the threshold
level applies only to surface water and there is a need to establish a groundwater to surface water
interaction for the threshold to be relevant. Since springs represent an interaction between
groundwater and surface water, we used the threshold level for comparative purposes. Figures
25 and 26 represent examples of changes in nutrients in springs of the SRWMD. Figure 25 is
an example of a decreasing nitrate trend. Nitrate significantly decreased from 1998-2003 for Poe
Spring. For comparative purposes the SRA was chosen as a fixed reference and is the gray line in
Figure 25. Poe Spring exceeded the SRA recommendations prior to 1999, but then declined to
levels below the SRA. Possible reasons for the decline in nitrate in the Suwannee Basin will be
discussed later.

While nitrate often decreased in the SRWMD, TKN rose significantly. Phosphorus also
exhibited some increasing concentrations. Total phosphorus at Poe Spring (Figure 26) almost
doubled from 1999 to 2003. Phosphorus and phosphate both increased at several springs. An
even greater number of upward trends, however, were seen for TKN. Figure 26 (bottom) shows
an increase in TKN at Lafayette Blue Spring over the study period. The plot also illustrates
some of the differences between nutrient and saline trends. While saline and rock-matrix analyte
plots give evidence of clear increases, trend lines for nutrient plots were sometimes less well
defined and potentially not as strong. Figure 26 shows a significant upward trend for total
phosphorus (MK test, p < 0.05) though the p-value of 0.0443 does not indicate such a strong
increasing trend; data for the first and second half of the time sequence were not significantly
different (WT p-value = 0.3633). The potential causes of nutrient and other trends will be
discussed later.

Figure 25. Decreasing nitrates at Poe Spring. The horizontal line represents
The FDEP's SRA limit for total nitrate (0.45 mg/L). Levels exceeded recommended
SRA limit prior to late 1999 but since then were significantly lower.

12

- 08

0

04

0 0

m m SRA Value= 0 45 mg/L

m m * .
F--^

BULLETIN NO. 69

Poe Spring Time Sequence C (1998-2003)

5/1/1997

1/30/1999 10/30/2000 7/31/2002

MKp-value <0.0001 SS = 0.0007
WTp-value 0.0001 n=i22 n2 23

Lafayette Blue Spring Time Sequence A (1991-2003)

U v

U-^

1/1/1995

6/18/1997

12/5/1999

5/22/2002

11/7/2004

MK p-value = 0.0443 SS = 0.0012
WT p-value = 0.3633 nB= 6 nc= 41

Figure 26. Increasing nutrient analytes at Poe and Lafayette Blue Springs.
Poe (top) and Lafayette Blue (bottom) illustrate two increasing nutrients in
the SRWMD: one for phosphorus and the other for TKN. Poe shows a clear
increase in phosphorus while TKN at Lafayette Blue illustrates one of the many
increasing TKN trends in SRWMD springs. Beginning and ending sampling
dates for these springs are not the same.

0.14

0.12-

--
0.10

I-
0.08 -

0.06 -

0.04 -

. .**

5/1/2004

0.4-

0.3-

0.2 -
I-

0.1 -

0.0-

- .-

FLORIDA GEOLOGICAL SURVEY

St. Johns River Water Management District

The springs located in the St. Johns River Water Management District (SJRWMD) and
used in this report are found in Figure 27. Spring names and abbreviations are found in Table 8.

Calcium, strontium, fluoride, and pH increased in a significant number of springs over
time Sequence A, while phosphate levels decreased. With respect to individual springs, Miami,
Palm, Sanlando, and Wekiwa Springs had at least eight analytes with increasing trends over
Sequence A, while Volusia Blue Spring (Vol Blue) and Sweetwater Spring decreased in at least
eight analytes over the same time sequence. Alexander, Salt, and Silver Glen (Silver G) Springs
each had six or fewer analytes showing any trend (positive or negative). Sequence B had no
districtwide trends. During Sequence C fluoride and pH increased in a large number of springs
while flow decreased at many locations.

Rock-Matrix and Saline Analytes

Increasing trends were associated with the following rock-matrix analytes: strontium,
calcium, pH and fluoride increased over Sequence A. Nine springs had significant increases in
calcium and pH while one spring had a decreasing trend for theses analytes. Both fluoride and
strontium increased in 10 springs. Strontium decreased in one, whereas fluoride decreased in
none. No trends were observed in Sequence B. Within Sequence C, upward trends were
observed for fluoride and pH, while flow decreased. Thus, major changes for the SJRWMD, like
other districts, occurred during 1998 to 2003 (Sequence C).

Figures 28-30 depict increases in two rock-matrix analytes for three springs in Seminole
and Orange Counties. Not depicted are Starbuck, Rock, and Apopka, which showed the same
pattern. Alkalinity and strontium suggest changing chemistries. Both analytes increased in
Palm, Sanlando, and Wekiwa Springs. All plots show trends closely fitting an increasing best-fit
line. Starting at about 116 mg/L for alkalinity, Palm Springs increases to about 126 mg/L.
Sanlando Springs begins at about 130 mg/L and increases to approximately 150 mg/L.
Strontium at Sanlando Springs began around 60 tg/L and ended over 90 with little variation in
the upward trend. Wekiwa Spring started at a higher level (near 100 tg/L) and ended the time
series at about 140 [tg/L. Wekiwa Spring is also unique in showing an apparently quick increase
in concentration between 1993 and 1995. Palm Springs differed from the other two springs in
having strontium concentrations at the start of the study three to four times higher than the other
two springs.

For the study period, there were fewer nutrients trends in the SJRWMD than in other
WMDs. For example, both phosphorus and TKN demonstrated few to no changes (no increases
or decreases for phosphorus, no increases and two decreases for TKN). Nitrate showed no clear
trend direction. For example, in the seven springs showing trends for nitrate, three increased and
four decreased. With respect to nutrients, only phosphate showed consistent trends across the
district. Eleven springs decreased in phosphate while no springs increased.

Figure 31 shows two phosphate trends, which also are considered to be Rock-matrix
analytes. Phosphate levels for both Palm and Starbuck Springs fell by nearly half of the initial
concentrations. Phosphate at Palm Springs (top figure) began the time series at approximately
0.15 mg/L and dropped to about 0.09 in 2002. Values from the end of the time series, 2002 to
2003, suggest a rise in concentrations. Starbuck levels began near 0.17 mg/L and fell to about
0.12 mg/L. Similar to Palm Springs, Starbuck appears to record a rise in concentrations near the
end of the time series in 2003.

Southwest Florida Water Management District

Figure 32 shows the locations of the springs in the SWFWMD. Table 9 displays the
corresponding spring abbreviations.

Note that after our analyses, the SWFWMD notified the authors and told us that they now
question the validity of using Boyette Spring data. They now believe it receives a significant
portion of its water from a nearby sinkhole (< 1 kilometer away) and much of the receiving water
is dairy waste (Morrison, 2000). Since the individual spring analyses were already completed,
we decided to keep the spring in the analyses. However, because of the point-source dairy
contamination, Boyette Spring data were removed from districtwide and statewide analyses.
Also, the SWFWMD was the only WMD to analyze for bicarbonate, rather than alkalinity.

The SWFWMD springs had strong trends in rock-matrix, saline and nutrient indicators.
Similar to the SRWMD, rock-matrix and saline indicators rose significantly. Unlike the
SRWMD, nutrient indicators showed different types of trends. Differences in behavior of
nutrients between the SRWMD and SWFWMD suggest regional differences exist between these
two areas. Similarities in rock-matrix and saline trends between the SRWMD and SWFWMD
suggest these trends extend beyond district boundaries. Some springs showed more changing
chemistries than others. Betty Jay, Boyette, and Tarpon Hole Springs had many analytes with
increasing trends. Buckhorn Main and Hidden River No. 2 Spring had a number of decreasing
trends. Those showing no trends among the analytes studied during time Sequence B included
Boat, Bobhill, Rainbow Swamp No. 3, and Wilson Head Springs.

Rock-Matrix and Saline Analytes

Strong increases in both rock-matrix and saline analytes were evident in springs in the
SWFWMD during time Sequence A. Analytes with increasing trends include bicarbonate,

Figure 31. Decreasing phosphate concentrations at Palm and Starbuck
Springs. Palm (top) and Starbuck Springs (bottom) illustrate the most
sharply decreasing nutrient (phosphate) in the district. Both springs show
substantial reductions since the beginning of the time series, with a potential
increase at the end of the series. Note samples were not collected until 1995.

calcium, chloride, potassium, magnesium, sodium, conductivity, sulfate, strontium, and total
dissolved solids. Of these, increases strongly attributable to rock chemistries were bicarbonate
and strontium. Regarding salinity, rises in sodium, chloride, and total dissolved solids were
observed. Analytes in common to both groups included calcium, potassium, magnesium, specific
conductance, and sulfate (which showed strong increases). Similar to other districts, Sequence B
had very few trends. The majority of the influence for these increases occurred during time
Sequence C.

Chloride increased in 18 springs. Figures 33-35 depict the chloride trends from several
springs in the northern SWFWMD along the Gulf Coast.

Springs occur from north to south along the Gulf Coast. Figure 33 includes two springs
from southern Marion County, one of the northernmost counties in SWFWMD. These springs,
Rainbow No. 6 and Bubbling Springs, increased in chloride concentrations, both springs show a
steady increase during the years of Sequence A. Both springs began with 3.0-4.0 mg/L of
chloride and ended the time series with approximately 5.0-6.0 mg/L.

For a couple of springs just to the south in Citrus County, the increase in chloride was
more dramatic (Figure 34). Hunters Spring (top) began the time series with approximately 50
mg/L of chloride. Values rose quickly at one point, more than doubling, and then declined.
Trotter Main (bottom) showed a similar pattern, though with sharper changes. Trotter Main had
values of approximately 50 mg/L near the start, as did Hunters, but then increased to nearly 250

Figure 33. Increasing saline analytes at Rainbow and Bubbling Springs.
Rainbow No. 6 (top) and Bubbling Springs (bottom) had significant increases
in chloride. Tests (p < 0.05) included MK for trend, WT on sequences B and
C, plus an SS calculation on rate of change. Beginning and ending dates for
these springs are not the same.

FLORIDA GEOLOGICAL SURVEY

Hunter Spring Time Sequence A (1991-2003)

110-

90-

-
70

C-

50 -

30 -

1995 1996 1997

' I I 1 1i
1998 1999 2000 2001
Date

2002 2003

MK p-value = 0.0005 SS = 1.5802
WTp-value =0.0033 nb= 12 n, -20

Trotter Main Spring Time Sequence A (1991-2003)

250 -

200 -

-J
0)150
E

1995 1996 1997
MK p-value 0.0001 SS
WTp-value 0.0009 nib
23

1998 1999 2000 2001
0.1133 Date
15 nc -

Figure 34. Increasing saline analytes for Hunters and Trotter Main
Springs. Hunter (top) and Trotter Main Springs (bottom) had significant
increases in chloride. Tests (p < 0.05) included MK for trend, WT on
sequences B and C, plus an SS calculation on rate of change. Beginning
and ending dates for these springs are not the same.

mg/L at one point-a five-fold increase. Figure 35 depicts chloride concentrations at Weeki
Wachee and Bobhill Springs. Weeki Wachee began the time series with only about 6.0 mg/L of
chloride and ended with a concentration of about 8.0 mg/L. Bobhill Spring began about 5.0 mg/L
and ended with about a 9.0 mg/L chloride concentration.

Flow

Flow data were available for only three gaging stations within the SWFWMD. While
there were inadequate data to make statistical conclusions for the SWFWMD, data from the
three' stations suggested possible declines similar to the SRWMD. Homosassa No. 1 flow levels
declined for the years 1996-2003 (Figure 36). Longer-term trends are depicted in Figure 37,
which further illustrates declines in flow. Since the 1960s, average yearly flow for Rainbow
Springs has declined (dark gray line indicates a timeline for Sequence A). WT tests between the
first and second half of the data series show a difference between the two data series. However,
for data representing time Sequence A, results do not indicate a significant difference. This
suggests that trends on the scale of this study (i.e., 13 years) may sometimes be missed in spite of
being part of a larger change (e.g. 40 years of data).

Long-term flow in Weeki Wachee Springs flow data (Figure 37, bottom) has an equally
interesting pattern. Although no regression is displayed, flow data going back to 1904 displays a
rise until the 1960s, followed by a decline until the present. Gray lines illustrate the time line for
Sequence A and that for post-1960. The range in flow during this time appears to be two-fold
(100 to 250 cfs). Such a pattern may reveal that short-period trends may be part of longer-term
cycles for groundwater; implications of this will be addressed later.

Nutrient Analytes

For Sequence A, nitrate increased strongly (19 springs with upward trends, only one
down), while ammonia, phosphate, phosphorus, TKN, and total organic carbon showed little
indication of trends. Since TKN, phosphorus, and total organic carbon decreased somewhat
(though not significantly) it seems to indicate that nitrate-nitrogen alone showed the strongest
increase for SWFWMD. All other analytes showed little change or even evidence of a slight
decline. Also unlike patterns seen in the rock and saline indicators, nitrate increased during both
sequences B and C. This is in contrast with the rock analytes which showed strongest activity
during Sequence C.

Figure 38 and 39 illustrate nutrient trends and their variability for SWFWMD. Hunter and
Magnolia Springs (Figure 38), illustrate clear increases in nitrate over Sequence A. Nitrate
increases occurred regardless of initial concentrations at the beginning of the time series. For
example, Hunter Spring (top) had a consistent increase from a low initial value (about 0.25
mg/L) to just under the SRA threshold of 0.45 mg/L. Hunter remained under the SRA value for
the time period. Magnolia Spring showed a rate of increase similar to Hunter (SS = 0.0046 and
0.0042, respectively). However, Magnolia began the time series with a higher starting value
(about 0.35 mg/L). The trend for Magnolia crossed over the SRA threshold (Figure 38, bottom,
gray line marks SRA value). Similarly Weeki Wachee (Figure 39, top), began the time series

BULLETIN NO. 69

with a value near 0.45 mg/L and increased to 0.8 mg/L by the end of the time sequence. All three
springs had similar rates of change yet differed in their initial concentrations of nitrate.
Homosassa No. 1 Spring Flow

Overall, TKN showed little activity (one trend up, four down for Sequence A). Figure 39
(bottom) shows a trend in TKN for Boyette Spring. It started with relatively low initial values
and was followed with a rapid increase in 1998. Values went from near 0.5 mg/L to over 3.0
mg/L in short period of time.

Field Analytes

Only two Field analytes demonstrated decreasing trends over Sequence A, pH and
temperature. The analyte pH decreased in 10 springs, while temperature decreased in eight. The
trends for pH largely occurred in Sequence C.

Wells

The wells used for this study are a subdivision of FDEP's Background Network. The
subdivision is referred to as the Temporal Variability (TV) Network. Although independent of
springs, it was believed that evaluating trends in wells would shed insight as to the chemical
behavior of Florida's groundwater. The TV Network subdivides wells into whether they are
confined or unconfined. Because of the small number of confined and unconfined wells per
WMD, for districtwide and statewide analyses, the wells were also combined into one pool (All).

FLORIDA GEOLOGICAL SURVEY

Decreasing trends in water levels and pH were often observed. Because of the drought, the
lowering of water levels was predictable. However, the decrease in pH was unexpected.
Plausible reasons for the declines will be discussed later.

Rainbow Springs Average Flow (1965-2003)

900

800

| 700

600

500

250

S200

0

150

100

3/30/1905

8/15/1932

1/1/1960

U

5/19/1987

Figure 37. Long-term flow trends at two SWFWMD springs. Rainbow (top) and Weeki
Wachee Springs (bottom) show historic changes. For Rainbow, points represent average
flow per year. Although no regression line on the graph, Weeki Wachee data since 1904
(bottom) showed a rise until about 1960 followed by a subsequent fall. Dark gray lines repre-
sent time line for Sequence A. (One cfs = 0.028 cms)

Figure 38. Increasing nitrates at Hunters and Magnolia Springs. Hunters
(top) and Magnolia Springs (bottom) illustrate the most actively increasing
nutrient trend in the district (nitrate). Hunters' increase remained below the
the SRA (0.45 mg/L). Magnolia Spring's increase in nitrate began below
the SRA and ends above it; thus it crosses a recommended limit. Beginning
and ending dates for these springs were not the same.

Figure 39. Increasing nutrient analytes at Weeki Wachee and Boyette
Springs. Weeki Wachee (top) shows a clear increase in nitrate in Sequence
A. Most of the time series for Sequence A included values above 0.45 mg/L.
Boyette (bottom) illustrates an unusual trend in TKN. TKN values sometimes
rose suddenly over a very short period of time in 1998. SWFWMD staff indicat-
ed the source of the TKN was probably from a nearby dairy waste lagoon.
Beginning and ending dates for these springs were not the same.

-J

0"
z

0.5 -

0.4 -

^ U.
*

S0
SRAValue = 045mg/L

10/22/2003

2/12/1990

BULLETIN NO. 69

Northwest Florida Water Management District

Northwest Florida wells (Figure 40) showed a lowering of water levels for Sequence A
(six of eight wells were down, with no increasing trends). Temperature increased in five wells,
while the analyte sodium and sulfate increased in four wells. No wells demonstrated downward
trends for temperature, sodium, and sulfate. The analyte pH decreased in four wells.

Figure 40. Location of wells within the NWFWMD.

Changes in sequences B and C reflected those in Sequence A. For Sequence B water
level fell (six of eight wells had decreasing levels, while none increased). Several wells also
showed increases in sodium (increased in four wells, decreased in none) and conductivity
(increased in five wells, decreased in none).

Unlike springs, where the main influences on the chemistries occurred during Sequence
C, the only notable analyte in well data demonstrating a change was pH. The analyte decreased
in six of eight wells studied (and increased in none).

Water Levels and pH

Figures 41and 42 illustrate several of these trends. The association of water level and pH
suggest a relationship between the two analytes and will be discussed later. A drop in water
levels occurred in both unconfined and confined wells. Confined aquifer Well 312 (Figure 42)
showed a 5 m (15 ft) decline over the period of record.

The locations of the SRWMD TV wells are displayed in Figure 43. Decreasing water
level trends were observed in the SRWMD. Temperature rose in Sequence C (seven increased
and none decreased). Trends in Sequence A suggested the same pattern as in northwest Florida:
declines in water level and pH.

Figure 43. Location of wells within the SRWMD.

Water Levels and pH

Over the period of record, water level and pH trends looked similar to other districts. As
two examples (Figure 44) of unconfined wells (Wells 1943 and 2465), a drop in water level
appeared to be accompanied by a decrease in pH. Note that Well 2465 had rapidly declining
water levels but a relatively slower change in pH. The water level decreased approximately 5 m
(15 feet) by the end of the study. Confined groundwater showed similar patterns. Figure 45
shows water level and pH falling simultaneously for wells 2585 and 2675. In Well 2585, the
water level drop is a minimum of 3 m (15 ft); some points in the early time series have
substantially higher water level values [18 m (60 ft)] and suggest the difference was even greater.
By far the most extreme water level difference was recorded was Well 2675. From a high point
of 27 m (90 ft) msl in 1994, water levels fell to approximately 9 m (30 ft) by 2003. This is
nearly 18 m (60 ft) difference is due to its location near the Alapaha River. Local karst features
create differences in water levels in response to rainfall. Like other wells in the district, Well
2675 experienced a decline in pH.

Figure 44. Decreasing pH and water levels in SRWMD wells (#1943
and #2465). Both wells are unconfined. Tests (p < 0.05) included MK for
trend, WT on sequences B and C, plus an SS calculation on rate of change.
The beginning sampling dates for wells are not the same. (One m = 0.3048 ft.)

iii PREFACE FLORIDA GEOLOGICAL SURVEY Tallahassee, Florida 2011 The Florida Geological Survey (FGS), is publishing as its Bulletin No. 69 (Revised), Regional and Statewide Trends in Floridas Spring and Well Groundwater Quality (1991-2003) (Revised), authored by Rick Copeland, Neal A. Dora n, Aaron J. White, and Sam B. Upchurch. After the publication of the original publicati on, several minor errors were discovered. Most errors were found in the st atistical tables. This bulletin summarizes the results of a multiyear cooperative investigati on on spring and groundwater quality between the Florida Department of Environmental Protections FG S and the Bureau of Watershed Management, Division of Environmental Assess ment and Restoration. The data presented will be useful to scientists, planners, and citizens in understanding the quality of Floridas groundwater resources. Jonathan D. Arthur, Ph.D., P.G. State Geologist and Director Florida Geological Survey

xi EXECUTIVE SUMMARY Background Over the past several decades, it has been observed that the flows in Floridas springs are declining and water quality is degrading. The pr imary chemical concern is considered to be increased nutrients, including soluble forms of nitrogen and phosphorus. The sources are predominantly from animal waste, human waste, and from the synthetic fertilizers used on lawns, golf courses, or for agricultural activities. In recognition of these issues, the Secretary of the Florida Department of Environmental Protection (FDEP) directed the formation of th e Florida Springs Task Force in 1999. The multiagency task force consisted of 16 scientists, planners, and citizens who were concerned about the environmental health of Floridas springs. By 2000 the task force made a series of recommendations to protect and restore Florid as springs. They are outlined in detail in Floridas Springs: Strategies for Pr otection and Restoration (Florida Springs Task Force, 2000). Two of the recommendations were to: (1) Implement springs monitoring programs to detect and document long-term trends in water quantity and quality (2) Conduct research that will allow ca use-and-effect relationships to be established between land use and water management activities. The purpose of monitoring is to both support research efforts and to confirm the effectiveness of spring protection efforts. As a direct result of the first recommendation, the Florida Geological Survey (FGS) took the lead in implementing a spring monitoring program. By 2004 it published the latest Springs of Florida bulletina descriptive overv iew of Floridas springs. The main purposes of this document are to : (1) determine trends in groundwater where sufficient data are available; (2 ) establish prototype methods for evaluating and reporting trends for future applications; and (3) enhance the effo rts of determining cause-and-effect relationships between anthropogenic activities an d the resulting spring-water quality and quantity on regional (water management district-wide) and statewide scales. The reas on for the latter is that many other publications have addressed the causes of tr ends on an individual spring basis. If we attempted to develop an exhaustive list of possibl e causes of trends for each spring, it could take many years to accomplish. We decided to emphasize regional and statewide scales. An endeavor of this nature has never been attempted. If re gional or statewide trends were found, the causes and possible solutions to those causes may become the highest priority water management issues. In order to fully comprehend the implica tions of trends in springs, a thorough understanding of the behavior of groundwater in wells is also necessary. In 1983, the FDEP began a statewide groundwater quality monitoring network (Florida Statutes 403.063). Scott et al. (1991) stated that the purpose of the networ k was to detect or predict contamination of Floridas groundwater resources. Currently, severa l thousand wells are incl uded in the network. However, a subset of the well s are conducive to trend analysis (the Temporal Variability

PAGE 14

xii Network, or simply the TV Network). Since the FG S was asked to evaluate data for trends from springs, it followed to simultaneously do the same for groundwater from TV Network wells. Approach The FGS spring monitoring program commen ced operations in 2001. For many of the springs, previous samples had never been coll ected, so long-term trend analyses were not possible. However, the FGS contacted each of the four northern water management districts (WMDs), the U.S. Geological Survey (USGS), and programs within the FDEP to request copies of their historical spring-water quality and quantity data. The en tities each graciously delivered data to the FGS for analyses. It should be noted that the South Florida Water Management District (SFWMD) had insufficien t data for trend analyses. The FGS obtained sufficient data, meeting preset criteria, from 58 springs and 46 wells for the period January 1991 through December 2003. For reference, the study was divided into three time sequences. Sequence A represents the entire length of the study (1991-2003). Sequence B represents the January 1, 1991 December 31, 1997 time frame, while Sequence C represents January 1, 1998 December 31, 2003. Th e two shorter sequences were used to assist in identifying and evaluating s horter-term trends. As it turn s out, Sequence B coincided with relatively normal rainfall, whereas Sequence C covered a time that Florida experienced an extended drought. The analytes (constituents of interest) for this report can be broken down into five groups: (1) nutrients, (2) saline (or salt-water), (3) rock-matrix (or ro ck), (4) field, and (5) other. Of these, the three major groups are nutrients, saline, and rock-matrix. Nutrients are compounds that are essential for the growth of living orga nisms. Unfortunately, high concentrations in spring-water can adversely affect th e biota in spring runs. Saline analytes are related to salts. The most significant sources of salt are from the ocean or deep groundwater in Floridas aquifers. High concentrations of saline compounds (e.g. sodium or chloride) can restrict the usage of water. Rock-matrix analytes have thei r sources in the aquifer material (e.g. limestones and dolostones). They occur na turally and, unless they occur in extremely high concentrations, are generally not harmful to our environment. The field and other analyte groups consist of miscellaneous constituents that are useful in explaining trends in other analytes. Think of a trend as a direction of moveme nt (Berube and Boyer, 1985). Although there are many secondary questions that pertain to trends, trend analys is can be broken down to one fundamental, primary question, over time, are conditions changing (getting better or getting worse), or are they remaining the same? One can think in terms of concentrations of water quality (measured by analytes) or water quantity (measured by flow or water levels). Subjective descriptionssuch as better, worse, and rema ining the sameare based on objective changes over time, or trends. Throughout this report the term significant refers to statistical significance. Some of the trends reflect very important ch anges in water quality, whereas some only represent relatively minor changes in water quality that are not i ndicative of impending problems. If, during our analyses, a trend was di scovered, it was based on statistical significance. That is, within a

PAGE 15

xiii predefined probability, we do not expect the tr end to occur randomly. Since not all of the audience of this report is familiar with the statistical procedures employed, we decided to simplify the procedures to the extent practical. Fo r this reason, most analyses were restricted to linear trends, using nonparametric techniques. Data were checked for seasonalit y, and if found, were deseasonalized prior to trend analys es using a method recommended by the U.S Environmental Protection Agency (EPA, 1989). Trend analyses were conducted using the Mann-Kendall test, while the rates of change over time were determined using the Sen slope (Gilbert, 1987). Results and Conclusions The most important conclusion to be derived from this report is that Florida springs truly represent the canary in the coal mine with re spect to assessing regional groundwater quality in Florida. As will be summarized, springs are appa rently much better at indicating over-all change in a groundwater flow system than wells. Monitoring wells only allow for the sampling of a discrete portion of the water in an aquifer. They limit detection to a particular depth interval and a relatively limited spatial extent. Karstic aquifers are especially limited in this respect as frac tures and cavernous conduits may direct water flow around or below the location of a monitoring well. On the other hand, the quality of water discharging from a spring is an integral of the water quality of the total flow system within a springshed. This water is de rived from deep and shallow flow systems and conduit and diffuse flow. Furthe rmore, the water quality, and fl ow, data are weighted according to the relative importance of the flow systems and chemical sources within the springshed. As a result, springs appear to be much better at de tecting regional changes in a springshed water quality than do wells. This conclusion is supported by the fact that water-quality trends were much more obvious in spring data than in well data. Springs Of the analyte groups, rock-matrix and saline analytes had the greatest frequency of trends. Both analyte groups showed strong negativ e correlations with sp ring flow. For example, as spring flow decreased saline and rock-mat rix analyte concentrations increased. The relationship was observed throughout the state. The greatest increa ses in the concentrations of rock-matrix and saline analytes occurred duri ng a drought that occurre d between late 1998 and mid 2002. There are several probable expl anations and all can be a result of the drought. First, during the drought there was less rainfall, and c onsequently there was less surface-water flow. In karst terrains, much surface-water flows di rectly to groundwater through sinking streams (swallets). Typically, this rapidly recharge d groundwater is transmitted in well-developed subsurface conduits. Thus, there is very little contact time with the aquifer matrix before it discharges from springs, and it tends to have lower concentrati ons of rock-matrix analytes. During a drought, there is a decrease in the propor tion of freshly recharged surface water. This, at least partially explains the correlation be tween decreased spring discharge and increased concentrations of rock analytes.

PAGE 16

xiv A second probable explanation is related to th e removal of older, sa line-rich and usually more mineralized water from storage, often in the deeper portions of the Floridas aquifer systems. Beneath the state of Florida lies a l ens of fresh water, which is replenished by rainfall. Freshly recharged water is flushed th rough Floridas karstic (sinkholes, caves, springs etc.) aquifers relatively quickly to springs. In contrast, the deeper water is older (Upchurch, 1992; and Katz, 2004). Because it has been in c ontact with the aquifer matrix for a relatively long period of time, the aquifer water has ha d a longer time to pick up dissolved matrix material constituents such as calcium and magnesium especially in the Floridan aquifer system. With longer residence times, the older water tend s to have higher concentrations of rock-matrix material. A third explanation is similar to the second. Older, mineralized residual saltwater, was never fully flushed from the rock interstices in some portions of Florida (Johnson and Bush, 1986). With less rainfall during the drought, the wate r levels in the aquifers were lowered, and the size of the freshwater len s decreased. With decreasing freshwater potentials (e.g., water levels) the deeper and older connate water ca n find its way upward toward aquifer discharge points, such as springs. Thus, during the drought, increased concentrations in rock-matrix and saline analytes were observed, along with decreases in spring discharges. The trends were statewide in scale. The magnitude of scale wa s the most surprising and most significant finding of the study. After the driest portion of the drought (2002) Floridas hydrologic conditions began to recover and the concentrations of both types of an alytes began to decrease, as rainfall, recharge, and spring flow began to increase. The inverse relationship between spri ng-water discharge, and both rock-matrix and saline analyte concentrations was also observed in a study by Katz (2004). In addition, Katz also found a pos itive correlation betw een concentrations of rock and saline analytes and spring-water age. Nutrients in groundwater discharging from springs were one of the most important concerns of the Springs Task Force. Evaluation of trends in this report revealed that nutrient trends in springs had an uneven, or patchwork, distribution acro ss the state. That is, both increasing and decreasing nutrient trends were common and were observed throughout Florida. This suggests that the trends were often related to local land-use and water-use activities. As such, most nutrient concentrations observed in springs are locali zed and should be analyzed in relation to the corres ponding springshed. Nitrogen and phosphorus comprised the most frequent nutrient exhibiting trends. Nitrogen in the form of nitrate (nit rate plus nitrite as N) had the greatest frequency of increasing (degrading) trends. However, some springs actually had decreasing nitrate trends. Phosphorus, as total phosphorus and orthophosph ate, had both increasing and decreasing trends, depending on the springshed. Note that decreasing nutrient tre nds are not necessa rily good news. During the drought, an important observation was that some nitrate concentrations had positive correlations with spring flow. One possible explanation is that nitr ogen can be stored in the soils of Floridas springsheds (Bruland et al., 2008). During the drought, soils ma y have stored the nitrogen

PAGE 17

xv originating from fertilizer appl ications and the nitrogen did not find its way to the groundwater regime. When rainfall conditi ons return to normal, the soil s will release th e nitrogen and concentrations in spring water will eventually increase. On a similar note, decreases in phosphorus in some areas may likewise not be a reflection of improved management. It is possible that the upward migration of older wa ter, with different chemistry, reduced the phosphorus concentrations in many springs. If s o, reduction of phosphorus could simply be a byproduct of mixing with deeper, higher pH water not an improvement in water quality. This mechanism is discussed by Hem (1985) and by Odum (1953). They indicated that the solubility of phosphorous can be controlled by pH. Disso lved phosphorous is generally more abundant in lower pH (more acidic) water. Conversely, highe r pH (more basic) water contributes to the precipitation of phosphate and lowers the c oncentration of diss olved phosphorous in groundwater. Wells Within Floridas aquifers, the flow paths of spring-water can potentially be from both deep and shallow sources. Convers ely, wells typically are drille d to a specific depth in an aquifer. Consequently, flow paths of well wa ter are from a much narrower thickness of the aquifer, relative to spring water flow paths. Although there are exceptions, most of the 46 wells used in this study generally tap only the shallower portions of the aquifers. The wells tend to be less than 30 m (100 feet) deep. Because of the shallower dept h, the older, deeper, and more mineralized deeper aquifer water had a lower probability of being observed in the shallow wells. Thus, rock-matrix and saline trends were not seen as frequently in wells as in springs. Nevertheless, decreasing trends in water levels within wells were common. In addition, pHa field analytehad a positive correla tion with water levels; as water levels in wells decreased, so did pH. A possible explanation for this positive correl ation is as follows. Well intake zones for most wells in Florida are generally set at spec ified depths below the lo west predicted aquifer water levels. This is done in order to guarant ee water to the well during drought conditions. During dry times the upper surface of the satu rated zone is lowered downward toward the uppermost point of the intake zone For the aquifers tapped by the 46 shallow wells used in this study, most recharge is from wa ter, typically rainfall, penetr ating the land su rface and moving downward through the soil to the groundwater regime. Rainfall has a lower pH than most aquifer water. The pH is lowered further as rainwater picks up car bonic acid as it moves downward through Floridas soils (Freeze and Ch erry, 1979; and Upchurch, 1992). Therefore, as the water table (or the potentiometric surf ace in confined aquifers) drops, generally the younger, freshly recharged water with lower pH ha s an increasing probabil ity of entering well intake zones. As such, the lowering of the water table is a potential cause for decreasing trends in pH values across the state during the drought. A detailed description of this hypothesis, along with other related hypotheses, is di scussed in the body of this report. Another field analyte that displayed a trend was well water temperature. Between 1991 and 2003, its temperature typically increased; the reason is believed to be an increase in air temperature. Air temperature increased acro ss Florida (Southeast Re gional Climate Center, 2006). Since the wells used in this report tend to be shallow, it is believed that well water readily

PAGE 18

xvi responded to air temperature chan ges. On the other hand, the s ources of spring water are from shallow and deep portions of our aquifers. Deep er water tends not to respond to changes in air temperature. Thus, spring water displayed fewe r temperature trends th an did well water. Concerns Rock-Matrix and Saline Indicators: Saltwater Encroachment Saltwater encroachment is the displacement of fresh groundwater by the advance of saltwater due to its greater density (Neuendorf et al., 2005). It can occur during a drought when recharge declines and the freshwat er lens shrinks in size. Over geologic time, it can occur with sea-level rise. It can also occur when ex cessive groundwater pumping causes the advancement of saltwater. Freeze and Cherry (1979) use the term saltwater intrusion as the migration of saltwater into freshwater aquifers under the influence of groundwater development (pumping). For this paper, we use the term intrusion to indicate a man-induced process and use the term encroachment to make no distinction between natural and man-made causes. Figure 1 (top) displays the unc onfined, surficial aquifer syst em. The saltwater/freshwater interface is repres ented by a transition zone. During a drought, the water table lowers, the transition zone migrates inland a nd the thickness of the freshwater zone (lens) decreases in size. In his work in northeastern Florida, Sp echler (2001) menti oned several possible mechanisms that can drive encroachment and in trusion. During the dro ught, they included: (1) the movement of un-flushed pockets of relict s eawater within the Floridan aquifer system, (2) the landward movement of the fr eshwater/saltwater interface, (3 ) regional upconing of saltwater below pumped wells, and (4) the upward leakage of saltwater from deeper, saline waterbearing zones through confining units. Th e latter can occur where the units are thin or are breached by joints, fractures, collapse features, or other structural anomalies. Examples are displayed in Figure 1 (bottom). During the 1999-2002 drought, the flows in ma ny springs decreased, and one spring (Hornsby Spring) stopped flowing altogether for a period of time. In addition to the decreased rainfall, there was an increased demand for gr oundwater (Verdi et al., 2006). The drought and the subsequent lowering of a quifer water levels resulted in decreasing spring flows throughout the state. The increased demand for groundwater during the drought exacerbated the problem in some of the springs. The increasing trends in rock-matrix analytes during the drought is an indication of a reduction in size of the fresh water lens underlying the state and an indication of saltwater encroachment. Because the concen trations of saline analytes increased almost everywhere in the state during th e drought, it is an indication that encroachment occurred on a statewide scale.

PAGE 19

xvii Figure 1. Schematics of freshwater/saltwa ter transition zone and possible mechanisms for saltwater/freshwater intrusion. Note Cooper (top) represents the saltwater/freshwater interface in the surficial aquifer system as a tr ansition zone, whereas Spechler (bottom) depicts it as a sharp boundary. Modified from Spechler (2001) Modified from Cooper (1964) surficial aquifer system intermediate confining unit Not to scale Not to scale

PAGE 20

xviii The 1998-2002 drought was one of the worst histor ical droughts to aff ect Florida (Verdi et al, 2006). Except for south Florida, during th e drought the deficit rainfall ranged from about 10 inches in southwest Florida to almost 40 inches in northwest Florida. In order to make up for the drought, groundwater pumping increased, largely fo r irrigation (Verdi et al., 2006). Because an increase in groundwater pumping occurred during one of worst droughts, it is likely that human-induced saline intrusion took place and c ontributed to the increase in saline and rockmatrix analyte trends. On a statewide scale, the ex tent and severity of the intrusion is difficult to quantify. However, within the northern portion of the SWFWMD, a water budget and a regional groundwater flow model indicated that the increase [0.3 cm/y r (+0.1 in/yr)] in groundwater withdrawals was less than 2.0% of the decline in recharge due to the decrease [18.3 cm/yr (7.2 in/yr)] in rainfall (Ron Basso, Southwest Fl orida Water Management District, personal communications). Nevertheless, intrusion should be a concern. If another drought of this magnitude occurs, depending on the amount of increased pumping, it could potentially have adverse effects on the long-te rm sustainability of Floridas groundwater resources. Nutrients The Florida Springs Task Force (2000) indi cated that Floridas springs face serious threats due to rapid and con tinuing population growth. The st ates increasing population has resulted in extensive land-use changes, increased demand for freshwater, and an increased use of fertilizers. As rainfall seeps through the soils, and moves the nutrients into Floridas underlying aquifers, it creates localized degradation in Floridas groundwater resources. A report regarding FDEPs Springs Initiative Program efforts (Florida Department of Environmental Protection, and Florida Department of Community Affairs, 2002) noted that nitr ates have increased since the 1970s. It also noted that over the past 30 years many of Fl oridas springs experienced an increase in nuisance algae and in vasive exotic aquatic plants. These plants tend to thrive on excess nutrients and decrease dissolved oxygen levels in spring runs. Analyses for the 1991-2003 time frame indicated th at trends in nutrient concentrations in Floridas spring-water increased in some spri ngs, while they decreased in others. It is encouraging to note that there are some decreasi ng trends. The fact that nutrients (especially nitrate) tended to increase is an indication that some land-use management practices warrants reevaluation. But as noted previously, the rela tionship of these apparent decreasing trends may be related to diminishing spring flow. Monitoring The current study revealed an inverse relationship between rock and saline indicators and spring flow. The relationship was observed across the state (Figure 2). Note that changes in spring-water quality often lag behind changes in spring flow. For detail, the smaller charts depicted in Figure 2 have been enlarg ed and can be found in Appendix A. Historically, the WMDs and the USGS have monitored spring-water quality and discharge. With the commencement of the Spri ngs Initiative, FDEP joined in the monitoring efforts. Considerable efforts were made to elim inate inconsistencies in monitoring activities. Unfortunately, at the beginning of the study, the effo rts were not always successful. Specifically, the WMDs, USGS, and FDEP did not always monito r the same analytes, use the same laboratory

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xix analytical methods, or collect fl ow data on the same date as chemical and biological data were collected. In addition, they often sampled at different frequencies. Al l these inconsistencies made statewide comparisons very difficult. The results of this investigation demonstrate that statewide monitoring must continue. For this reas on, it is hoped that, in the future, the state can find ways to minimize monitoring inconsistencies. Recommendations One of the most surprising and most significan t observations of this study was that rockmatrix and saline analytes were increasing almost everywhere in Floridas springs, especially during the drought of Sequence C (1998-2003). Saltwater encroachment is a hugely significant issue. Saltwater can restrict water use and negatively affect freshw ater ecology, and can adversely affect the long-term term sustainability of Floridas water reso urces. The relationships among rainfall, recharge, groundwater withdrawals, groundwater qua lity and levels, plus springwater flows warrant further research, as doe s the effects of global climate change. The concentrations of at le ast one nutrient (nitrate) in numerous springs have been excessively increasing since the 1970s (Florida Department of Environmental Protection and Florida Department of Community Affairs, 2002). One of the most visible changes in springwater quality has been the increase in nuisance algae and invasive ex otic aquatic plants. What is the relationship between the increases in nutrients and the nuisance plants? Further research is needed. In addition, land-use management practi ce modifications are needed in order to reverse the increasing trends. It is beyond the scope of this study to elaborate on the management strategies. For a detailed discu ssion of many of the available stra tegies, an excellent reference is: Protecting Floridas Springs Land Use Planning Strategies and Best Management Practices (Florida Department of Environmental Prot ection and Florida Department of Community Affairs, 2002). Spring-water quality is sensitive to changes in spring flow and to aq uifer water levels. Springs represent excellent natural sampling locati ons for monitoring saline encroachment. It is recommended that, to the extent practical, spri ngs should be incorporated into a statewide saltwater encroachment monitori ng network. The result s of the spring monitoring could then potentially be used to supplement well monitori ng networks that are often used for saltwater encroachment purposes. Although the monitoring of springs and wells is critical for the sustainability of Floridas water resources, not all analytes of concern are sampled. Synthetic organic, other supplementary analytes (supplementals), as well as biological indicators, should be included on the monitoring lists. It should be understood that supplementals are expensive to collec t and analyze, and for these reasons, they can only be sampled on a low frequency basis. It should also be noted that supplemental monitoring is often determined by s ite-specific issues. For example, pesticides may only be detected at certain times of the ye ar or in certain locales determined by land use conditions. Supplementals such as pesticides, synthetic organic compounds, and trace metals should occasionally be sampled.

xxi It is critical that evaluations of spring water and groundwater be cl early disseminated to the public as efficiently as practical. One effici ent method is the use of indices. Stock exchange indices have been used in the financial co mmunity for many years. Groundwater quantity indices are used by the Edwards Aquifer Authority in Texas. As an example, the authority use real-time water levels in the Bexar County Inde x well as an index (indicator) for the entire county. During dry times, as wate r levels fall, water restricti on measures may be invoked by the authority. When water levels rise the restrictions are lifted (E dwards Aquifer Authority, 2006). There are several potential indices that could be developed for use in Florida. If one or more indices were developed, they have the potential to become very useful in informing the public about the status of our springs. However, in order to be viable, buyin by both the public and scientific communities are essential. Hopefully, indices will be adopted in the future. It is essential that technical reports rega rding the results of analyses be generated frequently and in a relatively short time frame. It is acknowledged that it takes a considerable amount of time for an initial report to be genera ted. However, after the initial report, the lag time between sample collection and report generati on should reduce considerably. In addition, subsequent reports using similar interpretativ e methods could employ computer programs to create boiler plate reports as quickly as an alytical data are received from a laboratory. Standardized spring and well sampling throughout the stat e is a critical need. If standardization is achieved, analyses of trends in the future will be much easier to conduct. This in turn will make the resulting interpretations more comprehensive, and the dissemination of the interpretive results will be more me aningful to the public. Specific aspects of the standardization effort include: core and supplemental water-qu ality analytes and indi cators, data reporting, sampling and laboratory quality assurance, data management, data analysis, and assessment reporting, Recommendation Synopsis Research Determine the relationships between increases in nut rients and nuisance plants/algae Determine the best land-use management practice needed in order to reverse increasing nutrient trends Improve our understanding of the relationships among: (1) ra infall, (2) recharge, (3) groundwater withdrawals, (4) groundwater quality and levels, and (5) spring-water quality and discharge Develop a spring environm ental health report card. Monitoring Recognize the importance of springs in saltwater encroach ment monitoring and incorporate spring monitoring into that effort

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xxii Add supplemental analytes to spri ng monitoring lists on a periodic basis Develop spring water-quality and quantity interpretative reports on a regular basis Adopt area-wide randomized spring sampling on a periodic basis in order to produce a synoptic report of all springs in Florida Continue to use the Florida Water Res ource Monitoring Council to increase monitoring efficiency. Topics for discussion should include: core and supplemental water quality analytes and indicators possible development of a spr ing environmental health index possible implementation of the random sampling of springs sampling and laboratory quality assurance data management data analysis assessment reporting

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BULLETIN NO. 69 1REGIONAL AND STATEWIDE TRE NDS IN FLORIDAS SPRING AND WELL GROUNDWATER QUALITY (1991-2003) by Rick Copeland (PG #126), Neal A. Doran, Aaron J. White, Sam B. Upchurch INTRODUCTION Florida is blessed with some of the most spectacular springs in the world. There are estimated to be over 700 springs in the state. People have been attracted to our springs since before Florida became a state. From a scientific perspective, some of Floridas springs have been sampled for over a century. The FGS published its first Springs of Florida bulletin (Ferguson et al., 1947), which documented the chemical and flow data of th e major springs. The bulletin was revised in 1977 (Rosenau et al., 1977) and a new bulletin was generated in 2004 (Scott et al., 2004). In each revision, additional chemical data were presented. Unfortunately, as beautiful as the springs are, not all is well. As Floridas population continues to grow, water-use and land-use changes are reflected in our spring water. The quantity and quality of spring water are both changing, and at least some of the changes are directly related to human activities. Since the 1940s Floridas population has gr own from about two million to about 18 million in 2000. This means that Florida has increased its population by a rate of about 600 people per day for those 60 years. In fact, between the years 2000 and 2005, the net rate of increase has been over 700 peopl e per day (U.S. Census Burea u, 2006). In the year 2000, Floridians withdrew 3.14 billion gallons of groundwat er daily (Marella and Berndt, 2005). Marella and Berndt (2005) indicated that ag riculture and public supply accounted for over 82 percent of t he groundwater use. Based on these data, each person used over 150 gallons per day of groundwater. It is not surprising that an extensive increase in water use has followed Floridas population growth. Neith er is it surprising that there ha s been a noticeable decline in the discharge of many of Florid as springs and that the intensive land-use changes have been followed by a noted deteriorations in spring-water quality. Scott et al. (2004) mentioned that one of the most notable deteriorati ons has been the increase in nutri ent concentrations in spring water. While nutrients such as nitrogen and phosphorous are required by aquatic organisms for growth and reproduction, when the concentrations are found to be higher than natural levels, problems can arise. Since the 1970s concentrations of nitrate, a soluble form of nitrogen, have been found to be increasing in a number of Florid a springs (Florida Springs Task Force, 2000). Over the past several decades, flows in Flor idas springs are declin ing and water quality is degrading. The primary chemicals of concer n are nutrients, including soluble forms of nitrogen and phosphorus. In order to improve and prot ect our springs, the Florida Sp rings Task Force (2000) made a series of recommendations to the Governor of Florida. One was that Florida should implement spring monitoring programs in order to detect a nd document long-term trends in water quality. In addition, it was recommended that the state should condu ct research in order to determine the

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FLORIDA GEOLOGICAL SURVEY 2 cause-and-effect relationship between land-use and water-management activities, and the resulting changes in spring-water quality and quantity. As a result of the Florida Spring Task Fo rces first recommendation, the FGS was asked to evaluate historical spring data in order to detect and document trends in spring-water quality and quantity. This document reports the findings of analyses fo r trends in springs, using data from the Springs Initiative of FDEP, the WM Ds, and the USGS spring sampling programs. ACKNOWLEDGEMENTS The authors wish to acknowledge a number of individuals and to thank them for their assistance. From the Florida Department of Environmental Protection, Division of Environmental Assessment and Restoration, Bureau of Watershed Management, we would like to thank Gail Sloane and Jay Silvanima for suppl ying the authors with data from the TV Network and their miscellaneous assistance on numerous occasions. Laura Morse assisted in supplying quality assurance information. Debra Harring ton, Rick Hicks, Gary Maddox, Jay Silvanima, Chris Sedlacek and Paul Hansard (now with th e Colorado School of Mines) supplied numerous editorial comments during the course of the proj ect. From the FGS, we would like to thank Doug Calman, Rick Green, Tom Greenhalgh, Harl ey Means, Frank Rupe rt, Tom Scott, and especially Ellen McCarron, for their many helpful editorial comments. We would also like to acknowledge the e fforts of numerous people from the water management districts who supplied us with spri ng data and constructiv e comments regarding the document. In particular the authors would like to thank Kris Barrios, Angela Chelette, Tony Countryman, Kevin De Fosset, Tom Pratt, and Ni ck Wooten, from the Northwest Florida Water Management District (NWFWMD); Ron Ceryak and David Hornsby of the Suwannee River Water Management District (SRWMD); and Ron Basso, Eric DeHaven, David DeWitt, Joe Haber, Robert Peterson, and Roberta Starks from the SWFWMD. We would like to thank Brian Katz and Stuart Tomlinson of the USGS. Both individuals supplied data and other informati on that was invaluable to the pr oject. We would like to thank Dr. Xu-Feng Niu of the Florida State University, De partment of Statistics, for contributing to the section regarding statistical me thodologies and to Rich Smith, a graphic designer, who assisted with making many of the figures. FLORIDAS SPRINGS Scott et al. (2004) presented an excellent overview of Flor idas springs. Although they did not specifically evaluate trends, the au thors described hundreds of Floridas springs, including a description of thei r water quality. In doing so they described many aspects that control the water quality and quantity of groundwat er. With this in mind, their work can be considered a precursor to the present trend analysis document. With the authors permission, much of the following introduction from the sections labeled Floridas Springs to Differences in Spring and Well Water Quality are paraphrased from their work, Springs of Florida.

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BULLETIN NO. 69 3 Many terms relating to hydrogeology and springs may be unfamiliar to the reader. For this reason a glossary of terms is found in Appendix B 1. In addition, Appendix B2 elaborates on the sources of the analytes discusse d in this report, alo ng with the probable causes for the trends observed. Spring-water discharge comes primarily from th e Floridan aquifer system, which is also the states principle source of groundwater. The springs provide a window into the aquifer, allowing for a measure of the health of the aquife r. Chemical and biological constituents that enter the aquifer through recharge processes may negatively affect the water quality in aquifers, as well as the flora and fauna of springs and spri ng runs. The declines in water quality can be directly attributed to Florid as increased population and changi ng land-use patterns (Florida Springs Task Force, 2000). Classification of Springs Springs are most often classified on the amount of flow or discharge of water. The flowbased classification listed in Table 1 is taken from Meinzer ( 1927) (Table 1). One discharge measurement is all that is required to place a sp ring into one of eight magnitude categories. However, it should be understood th at each spring exhibits a va riable discharge, depending upon rainfall, recharge and groundwater withdrawals within their recharge areas. This can result in a spring being classified as a first magnitude spring at one point in time and a second magnitude at another. In the past, a spring assigned a magn itude when it was first described and continued with that magnitude designation even though the discharge may have changed considerably over time. To alleviate this confusion, the FG S (Copeland, 2003) adopted a system using the historical median of the flow measurements to classify a springs magnitude. Using the new system along with the Meinzer system, a springs magnitude is now based on the median value of all annual median discharge measurements for the period of record. Of the over 700 springs inventoried by the FGS, there are 33 first-magnitude spring s, 191 second-magnitude, and 151 third-magnitude springs. Most are located in th e northern portion of th e state (Figure 3). Table 1. Spring Magnitude. Discharge Magnitude Metric Units English Units 1 2.832 cms 100 cfs ( 64.6 mgd) 2 0.283 to 2.832 cms 10 to100 cfs ( 6.46 to 64.6 mgd) 3 0.028 to 0.283 cms 1 to 10 cfs ( 0.646 to 6.46 mgd) 4 0.0063 to 0.028 cms 100 gpm to 1 cfs ( 100 to 448gpm) 5 0.631 to 6.308 lps 10 to 100 gpm 6 0.063 to 0.631 lps 1 to 10 gpm 7 0.473 to 3.785 lpm 1 pint/min to 1 gpm 8 < 0.473 lpm < 1 pint/min cms = cubic meters per second lps = liters per second cfs = cubic feet per second pint/min = pints per minute mgd = million gallons per day lpm = liters per minute gpm = gallons per minute

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FLORIDA GEOLOGICAL SURVEY 4 Figure 3. Locations of Floridas springs (From Scott et al., 2004). A second spring classification system is also in use. The Florida Spring Classification System (Copeland, 2003) (Table 2) is based on an assumption that karst activities have influenced almost all springs in Florida. U nder this system, all springs in Florida can be classified into one of four cate gories, based on the spring's point of discharge. Is the point of discharge a vent or is it a seep and is the point of discharge located onshore or offshore? Since all springs are either vents or seeps, the classi fication can be simplified into the following categories. A spring vent is defined as an opening that concentrates groundwater discharge to the Earth's surface, including the bottom of the ocea n. The opening is signifi cantly larger than the average pore space of the surroundi ng aquifer matrix. A vent is o ccasionally considered to be a cave, and groundwater flow from this type of vent is typically turbulent. On the other hand, a spring seep is composed of one or more small openings in which water discharges diffusely (or "oozes") from the groundwater environment. Th e diffuse discharge originates from the intergranular pore spaces in the aquifer matri x. Flow from seeps is typically laminar.

FLORIDA GEOLOGICAL SURVEY 6 Figure 4. Offshore Springs (From Rosenau et al., 1977). Spring Recharge Basins In addition to the awareness of increasing tren ds in contaminants such as nitrate over the past several years (Figure 5), there has also b een an increased awareness on the drainage basins that supply water to Floridas gr oundwater and springs. The amount of water and the nature and concentrations of chemical constituents that di scharge from springs are functions of the geology, hydrology, weather conditions and land uses within the spring recharge basin. This type of basin, often referred to as a springshed, consists of those areas within groundwater and surfacewater basins that contribute to the discharge of the spring (Dehan, 2002; Copeland, 2003). The springshed consists of all areas where water can be shown to cont ribute to the groundwater flow system that discharges from the spring of inte rest. Karst systems fr equently include sinking streams that transmit surface water directly to the aquifer; the r echarge basin may include surface water drainage basins that bri ng water into the spring drainage from outside of the groundwater basin.

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BULLETIN NO. 69 7 Figure 5. Median nitrate concentrations in 13 selected first-magnitude springs. Springs are Alexander, Chassahowitzka Main, Fanning, Ichetu cknee, Jackson Blue, Madison Blue, Manatee, Rainbow, Silver, Silver Glen, Volusia Blue, Wakulla, and Wacissa #2 (From Scott et al., 2004). OVERVIEW OF THE HYDROGEOLOGY OF FLORIDAS GROUNDWATER Florida enjoys a humid, subtropical climate throughout much of the state (Henry, 1998). Rainfall, in the region of the major springs (Fig ure 1), ranges from 127 cm (50 inches) to over 152 cm (60 inches) per year. As a result of the climat e and the geologic fram ework of the state, Florida has an abundant supply of fresh groundwate r. Scott (2001) estimated that more than 8.3 billion cubic meters [2.2 quadrillion (2.2 x 1012) gallons] of freshwater are contained within Floridas aquifers. However, only a very small percentage of freshwater is available as a renewable resource for human consumption. The Florida peninsula is the exposed portion of the broad Florida Platform. The Florida Platform, as measured at the 200 meter (more than 600 ft) below sea level contour, is more than 483 km (300 miles) wide. It extends more than 240 km (150 miles) westward under the Gulf of Mexico, and more than 113 km (70 miles) under the Atlantic Ocean. The present day Florida peninsula is less than one ha lf of the total platform. The Florida Platform is composed of a thic k sequence of variably permeable carbonate sediments, limestone and dolostone, lying on olde r igneous, metamorphic and sedimentary rocks. The Cenozoic carbonate sediments may exceed 1,220 m (4,000 ft) thick. A sequence of sand, silt and clay with variable amounts of limestone a nd shell overlie the car bonate sequence (see Scott et al, 1991 and Scott, 1992b for discussion of th e Cenozoic sediment sequence and the geologic

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FLORIDA GEOLOGICAL SURVEY 8 structure of the platform). In portions of the we st-central and north-centr al peninsula and in the central panhandle, the carbonate rocks, predominantly limestone, occur at or very near the surface. Away from these areas, the overlying sand, silt and clay sequences become thicker. As the rocks sediments compacted and were subjected to other geologic forces, fractures formed. These fractures allowed water to move more freely through the sediments and provided the template for the development of Florida's many cave systems. There are three major aquifer systems in Florida, the Floridan, the intermediate and the surficial aquifer systems (Southeastern Geol ogical Society, 1986; Scott et al., 1991). The Floridan aquifer system (FAS) occurs within a thick sequence of permeable carbonate sediments (see Miller, 1986 and Berndt et al., 1998 for discussi on of the FAS). In some areas, it is overlain by the intermediate aquifer system (IAS) and the intermediate confining unit (ICU) which consists of carbonates, sand, silt and clay. The surficial aquife r system (SAS) overlies the IAS (or the FAS where the IAS is absent), and is composed of sand, shell and some carbonate. The vast majority of Florida's springs result from di scharge from the Upper Fl oridan aquifer system (UFAS), a subdivision of the FAS as discussed by Miller (1986). Typical natural recharge to the FAS originat es as rainwater. As the acidic rainwater percolates downward to the FAS, it is made slightly more acidic by carbon dioxide from the atmosphere and organic acids in the soil. Once in the FAS, the groundwater dissolves portions of the limestone and enlarges naturally occu rring fractures. The dissolution enhances the permeability of the sediments and forms cavities and caverns. Sinkholes are formed by the collapse of overlying sediments into the cavities. Occasionally, the collapse of the roof of a cave creates an opening to the land surface. See Lane (1986) for a description of sinkhole types common in Florida. Recharge to the FAS occurs over approximately 55 percent of the state (Berndt et al., 1998). Recharge rates vary from less than 2.54 cm (one inch) per year to more than 25.4 cm (10 inches) per year. Water entering the upper portion of the FAS eventually discharges from a spring. The water has variable residence times. Katz et al. (2001) and Katz (2004) found that water flowing from larger springs had a mean groundwater residence time of more than 20 years and may reflect the mixing of older and younger waters. Florida's springs occur primarily in the nor thern two-thirds of the peninsula and the central panhandle where carbonate rocks are at or near the land surface. Most of these springs produce water from the UFAS which consists of se diments that range in age from Late Eocene (approximately 36 38 million years old [my]) to mid-Oligocene (approximately 33 my). Miocene to Pleistocene sediments (24 my to 10,000 years) often are exposed in the springs. The geomorphology of the state, coupled with the geologic framework, controls the distribution of springs. The springs occur in areas where karst f eatures (for example, sinkholes and caves) are common, the potentiometric surf ace of the FAS is high enough and the surface elevations are low enough to allo w groundwater to flow at the su rface. Springs generally occur in lowlands near rivers and streams. There are a number of springs known to flow from vents within river channels and many mo re are thought to exist. Hornsby and Ceryak (1998) identified many newly recognized springs in the channels of the Suwannee and Santa Fe Rivers. Springs

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BULLETIN NO. 69 9 that have yet to be described have been f ound within the Apalachicol a River between Gadsden and Jackson Counties (H. Means, Florida Ge ological Survey, pers onal communication, 2004). Weather and climatic events affect the appear ance of spring water. For example, during periods of higher than normal precipitation, such as hurricanes, some springs may reverse flow. When this occurs, stream water flows into th e aquifers. During these times, spring water often has a dark appearance because of the presence of tannins from surfacewater sources. Once stream levels drop enough, the dark waters agai n reverse flow. When this occurs, discharge becomes much clearer. Dryer periods also affect the appearance of springs For example, during 1998 2002, Florida experienced a major drought w ith a rainfall deficit in places totaling more than 127 cm (50 in) (Verdi et al., 2006). The resulting reduction in recharge from the drought, along with the normal withdrawals, caused a lowering of the potentio metric surface in the FAS. Many first magnitude springs e xperienced a significant flow reduction. Some springs ceased flowing completely. The appearance of the springs also changed as river and lake levels declined reducing the size of the spring-wa ter body and exposing sediments along the banks. QUALITY OF GROUNDWATER AND SPRING WATER Natural Factors Affecting Groundwater and Spring-Water Quality Most of the Florida land mass is a peni nsula that is surro unded by saltwater. R elict saltwater also underlies the entire state. The reason for this is that the Florida Platform consists of carbonate rocks that were de posited in a shallow ocean. At the time of deposition, saltwater existed in their intergranular pore spaces. Gradually over geologic time, sea level was lowered relative to its position when the carbonate sediments were deposited. Through compaction and down warping of sediments on both sides of the Platform, a series of complex fracture patterns developed. The patterns are often reflected at land surface and have actually influenced the pathways of many of Florida's streams. Over geologic time, as sea level lowered, th e central portion of the Florida Platform was exposed to the atmosphere. As rainfall percol ated downward it eventually replaced the upper portion of saltwater in the developing aquifers w ith a freshwater lens. Today, the irregularly shaped lens is generally thickest in the cent ral portion of the state, where it is over 610 m (2,000 ft) thick (Klein, 1975). It becomes narrow to ward Florida's coastline. The base of the lens is typically a transitional rather than a sharp boundary. Groundwater in the deeper portion of the lens, and along the coasts is mixed with saltwater and ha s relatively high concentrations of saline indicators such as sodium (Na), chloride (Cl), and sulfate (SO4). Water discharging from Florida's aquifer systems and springs has its primary source from rainfall. Much of the rainfall reaching land surface flows overland to surfacewater bodies, evaporates, or is transpired by plants. However, a portion of th e rainfall percolates downward through the sediments, or enters sinkholes, where it recharges the aquifers. During its travel downward from land surface to the water table, a nd during residence within Florida's aquifer systems, many factors affect the water chemistry.

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FLORIDA GEOLOGICAL SURVEY 10 A long residence time may allow sufficient tim e for chemical reactio ns between the water and the aquifer rock. As such, water chemistr y reflects the composition of the aquifer rock. Typical residence times range from less than se veral days (in secondary produced caverns and sinkholes) to centuries (Hanshaw et al., 1965). A second factor affecting groundw ater chemistry is flow pat h, which is the length and depth of the path that the gr oundwater follows as it flows th rough an aquifer (Upchurch, 1992). In general, shallow, short flow paths (which are characteristic of the SAS) result in shorter residence times for chemical reactions to take place. Consequently, the total dissolved solid (TDS) content is less than in longer flow-path systems. If the flow path is long (on the order of tens of kilometers), such as commonly occurs in the FAS, reactions between rock and water become more probable and the TD S content of the water would be greater as a result of continued rock-water chemical reactions. Because of the residence time and the flow paths of the groundwater within an aquifer, the quality of spring water is typically reflective of the interactions of the major rock types in the aquifer and the groundwater itself. A third factor which is of particular intere st is intergranular po rosity (pores through which water passes between the individual rock ma trix grains). Even though Florida's aquifers have large, secondary cavernous pores spaces, mo st of the pores tend to be small (Upchurch, 1992). Fortunately, whenever the por es are very small, they act as filters for microbes, small organic substances, and clay minerals. In general, this results in naturally filtered groundwater that is very pure and desirable for both dri nking water and recreation. Unfortunately, some pollutants are not always removed and our aquifers can become contaminated. Differences in Springand Well-Water Quality The processes controlling the water quality in wells is very similar to those controlling spring-water quality with at least one major difference. Wells are often drilled to production zones as close to land surface as is economical. This is the situation for the wells used in this study, which are for the most part monitoring we lls. Monitoring wells tend be shallow (median depth 80 feet (24 m ) (Appendix C). Most water in these sh allow wells represents young, recently recharged water. On the other hand, be cause springs are major discharge points, springwater can be considered to be an integrator of water from the entire springshed. Spring water is a mixture of young, shallow, freshly recharged wate r and older water from the deeper portions of the aquifer. For this reason, sp ring water tends to be older th an the relatively shallow water found in the monitoring wells used in this study. Indicators of Groundwater and Sp ring-Water Quality Problems Spring water, while it resides in the aquifer, is considered to be groundwater. However, once spring water exits from the spring onto the ear th's surface, it is considered to be surface water. Because of this change, the question arises whether regulators should apply groundwater or surfacewater quality standards to the water. Primary and secondary standards with maximum contaminant limits (MCLs) may exist for an anal yte while the water is considered groundwater, but differ for surface water; or vice versa. Drinking water st andards are protective of human

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BULLETIN NO. 69 11 health while surface water criteria are protective of aquatic biota. Although several analytes fall into this category, Nitrate (NO3 + NO2 as N), and hereafter abbreviated NO3, is a good example. Based on drinking water criteria, nitrate has a gr oundwater threshold value of 10 mg/L (Florida Department of Environmental Protection, 1994). However, no numeric nitrate criteria exist for surface water, other than Class I surface water whic h is used for drinking water. The FDEP is currently developing criteria for spring water. Until legal numeric criteria are established for nitrates, it should be unde rstood that any reference to thres hold values in the following text simply infers potential water-quality problems. One of the more disturbing aspects about Florida's groundwater quality has been the documented steady increase of nitrate over th e past several decades (Jones et al., 1996; Champion and DeWitt, 2000; Means et al., 2003). An example is displayed in Figure 5 (From Scott et al., 2004). It shows that nitrate concentrations have a gr eater than 19-fold increase in nitrate concentrations in 13 se lected first-magnitude springs (Alexander, Chassahowitzka Main, Fanning, Ichetucknee Main, Jackson Blue, Madi son Blue, Manatee, Rainbow Group composite, Silver Main, Silver Glen, Volusia Blue, Waku lla, and Wacissa #2 Springs) between the 1970s and 2000. The natural background nitrate concentrations in Florida groundwater are less than 0.05 mg/L (Upchurch, 1992). During the 2001-2002 time fr ame, the FGS sampled 125 spring vents. Of the 125 spring vents sampled, none had nitr ate concentrations exceeding the 10 mg/L threshold for Class I surface and drinking water. Fifty-two of the spring vents sampled had nitrate concentrations exceeding 0.50 mg/L (42 pe rcent) and 30 (24 percent) had concentrations greater than 1.00 mg/L. Thus, over 40 percent of the sampled springs had at least a ten-fold increase in nitrate concentra tions above background and approxima tely one quarter of them had at least a 20-fold increase. The elevated nitrate concentrations may adversely affect the aquatic ecosystem in springs and spring runs. Further res earch is still needed and is currently being sponsored by the Springs Initiative Program. The FDEP is aware of the nitrate issues and has worked with other governmental agencies to develop a series of steps to reduce nitrate concentrations in groundwater and springs in the middle Suwannee River Basin where many of Florida's springs are located (Copeland et al., 2000). The FDEP Bureau of Watershed Management and the Florida Department of Comm unity Affairs are active in coordinating the development of spring protection measures. Another groundwater quality conc ern is the influence of sali ne water. Several springs have concentrations of chloride (Cl; a saline indicator) exceeding th e 250 mg/L threshold for drinking water. Springs with this type of wate r tend to be located along Florida's coast and along the St. Johns River. The ultimate source of the salin e indicators is from naturally occurring saline water within the FAS (Klein, 1975), or from sea water near Floridas coasts. When the concentrations of saline indi cators are increasing, it may be the result of: (1) natural circumstances such as drought, (2) the consequent upconing of groundwater within the FAS, or (3) lateral intrusi on of salt water due to incr eased groundwater pumping. Enterococcus and total coliform bacteria represent a third concern. It is generally believed that these bacteria originate in fecal matter from warm-blooded animals ( Jelinkova and Rotta, 1978). Total coliform concentrations in several springs has exceeded the

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FLORIDA GEOLOGICAL SURVEY 12 drinking water standard of four colonies per 100 ml (Flo rida Department of Environmental Protection, 1994). However, it has b een determined that these bact eria can complete their normal life-cycle outside of warm-blooded animals, especi ally in environments found in parts of Florida (Fujioka and Byappanahalli, 2004), thus the concen trations of fecal colifo rm may not necessarily represent a direct link to warm-blooded animal pathogens. Further research is needed before definitive conclusions can be made regarding the source of fecal bacteria. Another concern is concentrations of enterococcus and fecal coliform bacteria with regards to swimming. The Florida Department of Health has set beach sw imming standards and advisory thresholds for both organisms. To date, exceedances of the standa rds and thresholds in springs have not been a problem. Nevertheless, many residents swim in spring runs and these bacteria are a concern. SPRING SELECTION PROCESS Very little spring-water quality sampling, mo stly by the USGS, occurred until the 1940s. In 1947, the FGS published its first edition of Spr ings of Florida (Fergus on et al., 1947) which documented the water quality in the major springs of Florida. The document was revised in 1977 and many previously undocumented springs were sa mpled (Rosenau et al., 1977). It should also be noted that during the 1970s, the three norther n water management districts were formed. They were the NWFWMD, the SRWMD, and the (S aint Johns River Water Management District (SJRWMD). Within a few years, these WMDs, al ong with the USGS and th e already established SWFWMD, occasionally co llected spring-water quality samples. By the 1990s, the NWFWMD, SRWMD, SJRWMD, and SWFWMD had established periodic to regular sampling, often with the assistance of the USGS, of sp rings within thei r jurisdiction. Partially due to the sampling efforts of the WM Ds, in the 1990s it became apparent that the water quality in some of Floridas spring s was deteriorating. For this reason, in 1999 the Secretary of the Florida Department of Enviro nmental Protection directed the formation of a multi-agency Florida Springs Task Force to provide recommendations for the protection and restoration of Floridas springs. In late 2000 the Task Force made recommendations for the preservation and restoration of Floridas sp rings to the Secretary, and in 2001 the Florida Legislature passed the Florida Spri ngs Initiative. The Initiative authorized funds for FDEP to begin investigating the status of Florida springs a nd develop strategies for protecting them. As a result of the Initiative, the f our WMDs, FDEP, and the FGS have cooperated to monitor Floridas springs. The Springs Initiative has been responsible for the collection of spring-water quality since 2001. Beginning with that year, much of the data used in this report were obtained from Springs Initiative-sponsored samples. Methods of ev aluating the data used in this report can be used in the future to analyze the spring data curre ntly being generated as a result of the Springs Initiative. In the meantime, data of spring-water quality collected as part of WMD spring sampling programs were used for th is interpretative report. The FGS requested spring data from each of the four northern WMDs in order to analyze spring-water quality and quantity fo r trends. The districts delivere d available data to the FGS in 2002 and 2003. It was soon discovered the WMDs had only sporadically sampled their springs

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BULLETIN NO. 69 13 through the 1980s. However, beginning in the early 1990s each district had begun to sample springs in a semi-consistent manner. Even though data do exist fo r many springs, only 58 springs (Figure 6) were ultimately included in the analysis; one from the NWFWMD, 14 from the SRWMD, 15 from the SJRWMD, and 28 from the SWFWMD. Selection was determined based on the consistency of the data. As a work ing definition, we consider ed consistency to be the longest string of data in terms of time, along with the greatest number of analytes. We also wanted the largest number of springs to be includ ed that met our concept of consistency. With these criteria in mind we determined that th e time period from January 1991 through December 2003 represented the time in which the most consis tent data existed for the greatest number of springs. We realize that there are several springs that have decades of data. We also realize that since commencement of the Springs Initiative, many springs now have data, but the time sequences are short. As a re sult, our data interp retations are valid only for the 1991-2003 time frame. A discussion of analytes eval uated and frequencies of sampling will be discussed later. Figure 6 displays the location of the included springs in the analyses. A list of the names of springs, along with location inform ation, can be found in Appendix D. WELL SELECTION PROCESS In 1983, the Florida Legislature passed the Water Quality Assurance Act (Florida Statutes, 1983, Chapter 403.063). As a result, FDEP, with the assistance of the five water management districts, plus several counties (A lachua, Broward, Collier, Lee, Miami-Dade, and Palm Beach) established extens ive groundwater monitoring networks. The purpose was to document both ambient groundwater quality c onditions (Background Network) and to detect changes in Floridas groundwater quality resultin g from the effects of various land uses and potential sources of contamination (Very Intens e Study Area Network [Scott et al., 1991]). Both networks were in operation unt il 2000. A major subdivision of the Background Network was the Temporal Variability (TV) Network. The TV Ne twork consists of a series of strategicallylocated Background Network wells scattered th roughout the state. They are sampled on a monthly to quarterly frequency. Beginning in 1996, FDEP began a major rede sign of its water resource monitoring efforts. The purpose of the redesign was to characterize the environmental conditions of Floridas water resources and to determine if those conditions are changing over time. The revised network (The Status Netw ork) became operational in early 2000. A detailed description of the Status Network is presen ted by Copeland et al. (1999). Throughout the redesign process, the TV Network only had minor m odifications. The stated purpose of the redesigned network is to evaluate temporal variabili ty of Floridas groundwater quality and to determine whether concentrations of the sampled analytes are in creasing or decreasing over time. The TV Network consists of 46 wells (Figure 7); 25 wells mon itor confined groundwater and 21 wells monitor unconfined groundwater. The wells tap each major aquifer system and are scattered throughout each of Floridas five WMDs. As can be seen in Figure 7, some of the well locations represent

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FLORIDA GEOLOGICAL SURVEY 14 Figure 6. Location of springs analyzed in this report. (A list of the spring names can be found in Appendix C.)

FLORIDA GEOLOGICAL SURVEY 16 clusters of wells. Wells that monitor confined ground water are sampled quarterly (thought to have less temporal variability), whereas wells that monitor unconfined groundwater are sampled monthly. With respect to the WMDs, the NWFWMD has eight wells, the SRWMD has 10 wells, the SJRWMD has nine wells, th e SWFWMD has 11 wells, and the SFWMD has eight wells in the TV Network that had significant data for an alyses. A list of well names can be found in Appendix C, along with we ll construction data. METHODS This report uses a relatively simple methodology to determine the condition of spring and groundwater quality. Most analyses boil down to the single straightforward question, are conditions getting better, getti ng worse, or remaining the same ? Though this report is based upon several statistical procedures, all address this single question. With this simple objective in mind, additiona l elaboration is requi red to expand upon the connection with actual statistical tests and methods. First, si nce better and worse are subjective and qualitative questions, an approach that will quantify them is needed. Thus, a somewhat more objective and quantitative form of the above question becomes, for the 19912003 period of record, are the indicators d ecreasing, increasing, or remaining the same? This frames the question of quality in the terms of changing quantities between two end-points (i.e., the start and finish of a time peri od of interest); changes in quanti ties, such as flow and loading, can be objectively tested in a variety of ways. In order to test quantities, the last remaini ng questions are: (1) which quantities and, (2) over what period of time? These further condi tions must be defined. The first question is which quantities? For this report, as many indicators as possible were tested. This allowed the authors to ask questions of the largest possible scale; limiting the number of indicators only limits the possible number of observations and maximizing the number of observations allows the most comprehensive view of changes that might be of concern. Second, for the quantities examined an increase or decrease in concentr ation must be addressed over a time frame Therefore, in order to maximize the effectiveness of the analysis, the l ongest possible time seri es was chosen for as many springs as possible. In summary, the choice was for the longest possible time frame for data with the highest quality, for as many indi cators possible, and for as many springs as possible. Laboratory and collection met hodologies have varied over th e last several decades in the state of Florida. Variations include not onl y differences among WMDs, but even use of different laboratories by the sa me district, changes within la boratories, incomplete sampling intervals due to varying purposes and other reasons. Because of this the earliest starting point for which data quality could be uniformly assumed to be high (in this case 1991) was chosen; this created the longest possible time series for anal ysis (1991-2003) for as many springs as possible. Regarding the second question, for this report, we chose trend analysis to evaluate a given time series (between 1991 and 2003) for lin ear trends. Note that Urquhart and Kincaid (1999) mentioned that trends may deviate from st rict linearity. Nevertheless, they mentioned

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BULLETIN NO. 69 17 that if a trend is present, a linear trend will be present, regardless of the type of mathematical structure of the trend, e.g. cyclic, episodic, or a stair-step look. For this report, we were not only interested in detecting the presence of a trend we were also interested in a statistical method that was relatively inse nsitive to missing sampling points (e.g., gaps in data series), outliers, and, data th at seldom had normal (G aussian) distributions. Based upon these reasons, our choice for analysis was the non-parametric, Mann-Kendall (MK) test for trends. Discussions of the MK test and other statistical procedures used in the study, including the corresponding assumptions, are found in Appendix E. Our last clarification involves interpretation of trends; n ot all increases are bad nor are all decreases good. For example, a decrease in nitrate is desirable and is considered to be good. On the other hand, a long-term decrease in flow is not desirable, since it may indicate an overuse of the resource. Thus, it can be considered to be ba d. Another example, an increase or decrease in pH may not be considered to be good (if it is extr eme), since this analyte is best defined by an optimal middle range; being far outside that range on either side is bad. The point is that change, in one direction or another, can be tested and the result ha s implications regarding the improvement or degradation of the system in question. Definition of Trends Natural systems in general undergo two main t ypes of change: cyclic and linear (A and B, top of Figure 8). Cyclic change is common in nature. Two common examples of cyclic changes include diurnal and seasonal ch anges. Natural changes can al so be linear, moving conditions from one state to another without re turning to the original state. The focus of this report is to document linear trends in water qu ality and quantity. It is also assumed that trends in certain analytes are most likely an thropogenic, rather than natural in origi n. In this case, three possible linear trend scenarios can be test ed. In each case, a chemical component of a groundwater system (whether spring or well) can be plotted as a concentration against time (Figure 8, bottom). The first scenario (on the left) is that the system is increasing in concentration for a particular analyte (for which the symbol, +, will be used in this report). One case could be phosphorus. Over a period of interest, change of concentration can be tested at a specific leve l of confidence (e.g., at a 95 percent confiden ce level, or an level of 0.05). This means that by the end of the time period, the concentration was high enough to warra nt the designation of being higher than expected by chance fluctuation alone. Such valu es are marked as being highly unlikely to have occurred unless notable changes to the system were introduce d. In the opposite case (on the right), the concentration could have decreased significantly (represented by -). Such a trend suggests a substantial change to the physical environment and w ould therefore be recorded. The third scenario (middle chart) is that neither case was observed. As will be detailed below, this is not a positive statement affirming uniform conditions for the system in question; rather it is a general category for all conditions not classified within the former two situations. This is a default option and it is likely that a number of valid trends that could escape detection and be included in this scenario.

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FLORIDA GEOLOGICAL SURVEY 18 Figure 8. Illustration of three op tions for water-quality trends. Trends can either increase (+), decrease (-), or otherwise cannot be confirmed. Depending on the analyte, the interpretation is that the system is getting better, getting worse, or remaining the same. Taking the example of phosphorus, if the trend is increasing, the situation is getting worse. If the trend is decreasing, it is getting better. Finally, if neither, nothing can be confirmed. All analyses in this report are assigned to one of these three observations. Problems with Trends Trend analyses were largely straightforward and posed few problems. Visual analysis of time series plots showed that the majority of significant trends were ba sed on a large amount of data that indeed demonstrated an obvious tendency. However, several exceptions arose and their handling is addressed in the following sections. Remaining the Same Possibility of Missed Trends The last case scenario in the phrase getting better, getting worse or remaining the same leaves a question as to the identity of the la st category. Note that the last observation remaining the samecannot be addressed sta tistically. It is therefore, considered the alternative case to the situa tion of an increasing or decr easing trend. Because of this remaining the same amounts to a catch-all for all remaining observations (i.e., trends that neither increased nor decreased). Though simple in principle, a clarifica tion should be stated. Within this last category re mains interesting, important, and valuable informationcycles, interesting structure, nonlinear trends, or other phenomena. More problematic, it is likely the analyses conducted here missed a number of trends (due to the st rict confidence limit). Increasing Trend (+) Unable to confirm Decreasing Trend (-) 3 observations for trends: Variable Time 0510152025 -6 -4 -2 0 2 4 6 Time (years)Concentration (ug/L) B. Cycle A. Cycle 0510152025 0 10 20 30 Time (years)Concentration (ug/L) A. Trend B. Trend

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BULLETIN NO. 69 19 However, it is important to state once again that the purpose for this study was neither to find all the trends possible, nor to find the largest number of trends; rather, the purpose was to identify all the trends that could be confidently, statis tically labeled as suc h. Other studies employing greater power (i.e., ability to detect more tr ends) could, and probably should, be conducted. But since this is the first such statewide analysis of water-quality trends, the goal was to minimize the number of false trendswhile maximizing the number of true tr endsin order to get the best picture of where the clearest problems exist. Outliers Statisticians often encounter data that lies outside of an expected range of values. The reasons for this may include data transmission errors, failed laboratory analyses, contaminated samples, and sometimes accurate data record ing unusual situationscauses are not always visible to analysts. This report was no exception. Technically, there are really only two ways of dealing with such data. One is to set arbitrar y guidelines in advance a nd handle the data in accordance. This may include removing outliers that occur above or below a certain accepted range, e.g. adjust the data. The other approach is to include all outliers in the dataset and analyze the data regardless. The rationale is that well-maintained data so metimes records outliers but, with sufficient data, the effects will be minimal. This report chose the latter option and included all data in all analysesnone were discarded. Their presence was accounted for and accommodated in several ways. The first was simply by the choice of analysis. Nonparametric statistics are relatively insensitive to the influence of extreme data points (outliers). A large number of bad data points can still influence even a nonparametric analysis. Cross-checking results and examining raw data can assist with this j udgment. In order to compare and check the influence of outlying data, every nonparametric statis tical trend test [the Mann-Kendall (MK) will be di scussed later] result was checked against a linear regression (parametric test) of the same data. Further, both analyses were co nducted with different statistical packages: Minitab (Minitab, 2003) for MK and SPLUS (S-PLUS, 2003) for cross checking regression analyses. Visu al examination of each individual time series was conducted to corroborate the results of the statistical tests; suspicious data sets were re-analyzed. Inspections revealed that in the vast majority of cases, reported statistical trends were composed of time series that showed clear visual trends Comparison of MK results to linear regressions (though parametric) showed surprising similarit y. Not only did the non-parametric MK results closely match the parametric analyses, but both were surprisingly unaffected by outliers; thus providing strong confirmation that both the data was of high quality and that it gave robust signals. Detection Levels Though the data used in these analyses were the best available in terms of quality assurance, other factors had to be considere d. The analysis of outliers demonstrated that consistency of data handling, laboratory repor ting, and subsequent quality assurance was good. Yet an additional issue surfaced in the plotted time series: the effect of laboratory detection limits. For statistical purposes, if a samples concentration was below the laboratorys method detection limit, it was considered to be the de tection limit. For example, where improvements in

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FLORIDA GEOLOGICAL SURVEY 20 laboratory methodologies over time lowered the mi nimum detection value for several analytes, trend analyses detected significant downward tre nds where no such trend existed. Indeed, a number of time series plots revealed that a nu mber of trendsstatisti cally significant by MK testswere actually the artifact of such stair step patterns trending down over time (Figure 9). All data series, therefore, were checked visu ally for such spurious results. Those data series found exhibiting such results were remove d from consideration in the final analyses. These were assigned the designati on DL (detection level) in result tables (e.g., plus-minus charts which will be discussed later); trends created by detection level artifacts were removed from further analysis. Figure 9. Example of a spurious trend. Detection limit changes can generate the appearance of false trends. All time series for all analytes were visually checked for aber rant results since visual inspection was was necessary to identify artifacts. 2/12/199011/8/19928/5/19955/ 1/19981/25/200110/22/2003 Date 0.00 0.05 0.10 0.15 0.20F (mg/L) Well 1943: Example of Detection Limits

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BULLETIN NO. 69 21 Sparse Data The quantity and consistency of existing data varied widely depending on sampling agency, analyte, and location of springs or wells. Given the amount of data used for the time series studied herein, a distinction should be made concerning how the quantity of data affected its quality First, all reported analyses had sufficient da ta for time series analysis. Sufficient data constituted a minimum of 10 points for the entire series. Many so ftware packages would not generate statistical results without a minimum set of pointswhich was often 10 values. At the same time, there is a difference between what constitutes a sufficient amount of data and how that (sufficient) quantity is structured through time. The former issue concerns whether an analysis could be conducted while the latter has implications for the reliability of the interpretation. On one end of the spectrum, some locations only had 10 values, while at the other some had in excess of 100 values. As it tu rns out, considering both springs and wells, the median number of data for the 1991-2003, Sequence A, time frame was 38. Long-term, consistent data collection is an ideal situation for analysis. However, most data sets were between the extremes of a lot or too little. Much of the data used here can be described by the term sparse data which we use to mean there are not very many data points in the time sequence but there were a minimum of ten. Often the spring data were collected for some other purpose than for time-series analysis having little structure at all. This results in messy data. Messy or disorderly data include s missing values, outliers, transcription errors, or extreme and skewed results. Simply stated, a high proportion of time sequences have varying amounts of missing data. The missing data hinders reliable data interpre tation. One example of messy data is nitrate concentrations at Wakulla Spring (Figure 10). An example is as follows. Suppose a large number of data points exist at the beginning of the ti me series, nothing in the middle, and one point at the opposite end of the se ries. Also, suppose a trend is detected. The problem with such a trend is that although it is statisti cally valid, it may be entirely dependent upon the single point at the one end of the series. If such a tre nd is labeled valid, then poor judgment was used. The best interpretation for a trend exists when th ere is an abundance of points sampled consistently for the longest period of time. Time gaps in data series were the most common problem. In a number of cases data collected early in the time series were followed by one or more data colle ction gaps of varying temporal duration. Such trends are dependent upon the connection of two (occasionally more) clusters of data. Though the trends may be valid, they are not ideal; this example underscores the necessity for sampling agencies to implement consistent collection plans over the long term. Though the data can often be used, its utility can be challenged, or c onsidered suspect. The reason is that the value of any individual data poin t is a function of the number and reliability of nearby data points to which it can be compar ed over the long term. Da ta that are sparse, inconsistently collected, or have large time gaps ar e substantially less valuab le than a consistent,

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FLORIDA GEOLOGICAL SURVEY 22 Figure 10. Example of sporadic, unsystematic, and incomplete sampling. Only seven points were collected in the final eight years of this Wakulla Spring study. Sparse, inconsiste nt sampling after 1994 meant the trend seen here was dependent on relatively few points collected in 2000. Though the trend is statistically valid, this is an excellent illustration of the need for consistent longterm data collection. Ironically, though budget issues are often responsible for gaps in sampling, note that missing data greatly reduces the value of points remaining. Note no data were obtained after 2001 even though Sequence A continued through 2003. well-documented time series. Sparse data collecti on was a significant issue in several notable springs. For example the trend for nitrate at Waku lla Spring for Sequence A included a six-year gap (1994-2000) during which th ere was only one sample coll ected. Although th e statistical conclusion that nitrate concentrations at Wakulla were decreasing is valid (to be discussed later), with the lack of data during the 1994-2000 time frame, some may doubt the interpretation of a decreasing trend. Incomplete data sets existed for many analyt es and indicators. Time series for some analytes (e.g., iron) only had a handful of points over the 13 years. For such very small sets, trend analysis was meaningless and th ese were excluded from analysis. ANALYTES AND INDICATORS A total of 48 chemical constituents and indicators, with a period of record 1991-2003, were analyzed for this study. A list of analyt es and their correspondi ng STORET codes can be found in Appendix F. Data were obtained from several different sources. The state water management districts offered the most info rmation, followed by FDEP and the USGS. Each agency used their respective sa mpling and analysis procedures under whatever gu idelines that were being followed for that part icular period of time. This comp licated the statistical analyses. However, identification of useful data led to a fi eld of 48 different analytes of water quality with

BULLETIN NO. 69 25 SJRWMD, the SWFWMD, the SFWMD, and the FDEP. In addition, multiple analytical laboratories were used to process the samples. For the 1991-2003 time sequence, spring sampling and analyses faced all of the potential aforementioned problems. During the same time peri od, especially during th e early days of the operation of the TV Network, well monitoring encountered many of the same problems that spring monitoring encountered. The TV Netw ork is operated by the FDEP and by the mid 1990s, the FDEP reduced a considerable portion of unwanted variability by adopting a policy of using a standardized sampling pr otocol, a standardized method of sample transport, a single analytical laboratory, and a standard set of anal ytical methods and reporting protocols. It is hoped that one day, spring monitoring throughout Florida will also adopt similar protocols that will reduce variability. In spite of the potential variability, not all is negative. For all water samples and data used in this report, each corresponding sampling agency and/or analytical laboratory has an individually-approved quality a ssurance/quality control (QA/QC ) plan on file with FDEP. Regarding QA/QC, the contact for each WMD, FD EP, and the USGS are found in Appendix G. It should be noted that by 2001, in an effort to achieve standardization, the FDEP adopted a recommended method for spring-water quality sampling. An overview of the protocols is found in Scott et al. (2004). The TV Network is managed by the Watershed Monitoring Section (WMS) of the FDEP. It recent ly produced an overview of its well water sampling protocols (Florida Department of Envi ronmental Protection, 2003). Analytes used in this study Multiple agencies collected water-quality samples for th is publication; however one agency may have sampled one analyte, while anot her agency sampled a similar analyte that was closely related to the first. This was quite co mmon for the analytes nitrate, ammonia, phosphate, phosphorus, magnesium, sodium, potassium and chloride. Most often, the difference was between the collection of the dissolved (filtered sa mple) and total (unfiltered sample) form of the analyte. It would be preferable if sufficient data in both the disso lved and total forms of these analytes were available. Unfortunately, it was no t always the case. It was decided to combine the total and dissolved forms becau se of the importance placed on nutrients in order to obtain a time series with a sufficient number of data valu es. We do not recommend this procedure in the future because it would be better to use one or both of the forms in conducting statistical analyses. In the recommendations section (discussed later) we recommend a more consistent set of analytes be used in the future. Neverthele ss, for this study, we occasionally used a combined surrogate form of nitrate, ammonia, phosphate phosphorus, magnesium, sodium, potassium and chloride. We did this solely for the purpose of obtaining a sufficient amount of data necessary for data analyses. Grouping of Analytes For convenience, and in an effort to better understand groundwater quality trends, the analytes (or indicators) were di vided into several groups. They are: (1) Field, (2) Rock-matrix

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FLORIDA GEOLOGICAL SURVEY 26 or Rock, (3) Saline or Saltwat er, (4) Nutrient, and (5) Other analytes. However, because of occasional chemical complexities, many analytes are grouped into more than one category. Table 5 lists them by group. Note that analytes in the table only refer to those that displayed trends. A detailed description of eac h analyte is found in Appendix F. Table 5. Analyte Groups Field Rock-Matrix (Rock)* Saline or saltwater Nutrient Other Discharge Alk Ca Ca and Mg TSS DO Ca Cl K Turb pH F K N TOC SC Fe Na NH3 and NH4 Temp K SC NO3 or NO3 + NO2 WL(msl) or Stage Mg SO4 PO4 and P PO4 and P TDS SO4 SC WL(msl) or Stage TKN SO4 TOC Sr pH *Light gray indicates common rock and saline-related indicators while dark gray shows common nutrient analytes. Descriptions of Analyte Groups Each analyte represents a measur e or variable that can be us ed to assist in judging the overall health of Floridas groundwat er. Field analytes such as di scharge, water level, and flow describe quantity, but they can also greatly affe ct quality. The rock analytes suggest upconing of water from deep within Floridas aquifers. The saline analytes suggest intrusion or upconing of water from the deep portions of our aquife rs, and the nutrient analytes are those that stimulate biological growth or are present as a direct result of biological activity. Field Analytes Field analytes represent a gr ouping for convenience. Measur ements of field analytes were conducted prior to collecting samples for laboratory anal yses. The analytes in this group that were used for trend analyses include: discharge (or flow), dissolved oxygen (DO), pH, specific conductance (SC), water temperature (Tem p), and water level [water level relative to mean sea level (msl) based on the North Am erican Vertical Datu m (NGVD) of 1988)]. Rock-Matrix Analytes Rock-matrix analytes are those indicative of the rocks making up an aquifer. Because of natural rock weathe ring, water that has had a long residence time in an aquifer system has a

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BULLETIN NO. 69 27 greater probability of having a high concentra tion of dissolved rock matrix material. Rock indicators include: alkalinity (Alk), calcium (C a), magnesium (Mg), plus to a lesser extent, fluoride (F), iron (Fe), pH, potassium (K), strontium (Sr), sulfate (SO4), phosphorous (P), orthophosphate (PO4) and SC. Since phosphate a nd phosphorus are often found in the mineral fluorapatite, these two analytes are also included in the rock-matrix group. Saline or Saltwater Analytes Saline analytes are those associ ated with salts within either connate water or seawater. Connate waters are those waters trapped within th e sediments at the time of their deposition. Since the original sediments were deposited in a marine environment, the pore spaces contain very old saltwater. Saline analytes are obviously also found in the seawater located along Floridas coasts. The major difference is the age of water. High c oncentrations of saline analytes are often an indication of horizontal saltwater encroachment. However, they can also be an indication of encroachment of highly mineralized water from th e deeper portion of Floridas aquifers, below the fresh-water lens. The encr oachment can be caused by the depletion of the less dense fresh-water lens during a very dr y period (e.g. a drought), or by the upconing of connate water during periods of heavy groundw ater withdrawals. Pumping of groundwater increased during dry periods and th is process exacerbated the appare nt intrusion process. Saline analytes include: calcium, chloride, potassium, sodium (Na) specific conductan ce, sulfate, total dissolved solids (TDS), plus water level (MSL) and stage. Nutrient Analytes Nutrients represent naturally occurring compounds or elements that are essential for the growth of living organisms. However, if found in high concentratio ns, over-enrichment of nutrients (eutrophicat ion) in a body of surface water can lead to an overgrowth of plant life (including algae) and possibly a loss of dissolved oxygen. For th is report, nutrient analytes include: organic carbon, phosphate, phosphorus, a series of nitrogen related species, and to a lesser extent, Mg, Ca, K, and sulfur in the form of sulfate. The nitrogen related species include nitrogen, ammonia, total kjeldahl nitrogen, nitrate, and nitrite. Other Analytes Analytes in the other category do not fit in any of the other four categories. They represent a miscellaneous group. For trend anal yses, the analytes incl uded in this group are suspended solids, and turbidity. DATA The original data were from several sources The data used for the trends analyses discussed in this document are in Appendix H.

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FLORIDA GEOLOGICAL SURVEY 28 Data Sources The majority of the water-quality data from the springs were collected and analyzed by the water management districts. The data for wells were obtained from the FDEP Watershed Monitoring Section. Data Verification The analysis of the data was verified severa l times with processes including internal and external reviews in addition to repeat analyses by each author. The internal review consisted of audits performed by two of the authors (N. Dora n and A. White). These audits included handeye verification of every analysis figure for accu racy. Repeat calculatio ns were performed and compared with the first value made using new va lues calculated from the original data. When errors were found, the data were r ecalculated by at least two of the co-authors and then replaced. The external verification was conducted through multiple meetings with WMD staff. During these meetings many of the actual samplers a nd initial compilers of th e data were present. Two rounds of discussion took place; once before this document was comp iled and again as it neared completion. These meetings lasted for several hours and many comments were made on procedures and verification policies. Each concer n was subsequently addressed and is exhibited in the subsequent sectio ns of this document. Data Preparation Preparing the data for analysis included a ddressing the problems of seasonality, missing values, duplicate data, censored data and detect ion limits. The data variation caused by seasonal cycles increases the difficulty of detecting long-te rm trends. This problem can be alleviated by removing the cycles before applying tests or by using tests unaffected by the cycles (Gilbert, 1987). Missing values (i.e., samples that were never collected) cause their own special difficulties for analysis. For example, suppose 12 monthly water samples were scheduled to be collected from a selected well in a given year. Suppose that for a variety of reasons, only 10 were actually collected. Thus, the well had tw o missing values for each indicator sampled. Unless otherwise stated for the statistical analyses missing values were treated as if they were never collected. For example, if only 10 samples were collected, then descriptive statistics were based on 10, instead of 12 samples. Duplicate data resulted from two samples collected from the same spring or well consecutively. The two samples were then labeled as representing two different sampling events and sent to a laboratory for analyses for the same set of analytes. The purpose of duplicates is to evaluate the internal precision of a laboratory. For statistical analyses, it was decided that the primary sample, collected first in the time sequence, would be used. The second duplicate sample was only used for quality assurance evaluations.

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BULLETIN NO. 69 29 The minimum detection level for analytes from analytical laboratories can cause environmental data to be censored. That is, the distributions are truncated at their lower ends near the laboratory detection level. As stated ear lier, for statistical analys es, all data reported as Below Detection Level (BDL) were arbitrarily set at the detection level. In addition, it should be noted that for a given analyte, over the peri od of record, the labora tory detection levels changed, giving multiple detection limits. Time Sequences Data for analyses were segmented into three time sequences: Sequence A (1991-2003), Sequence B (1991-1997), and Sequence C (1998-2003). The first sequence spanned the entire sampling period, January 1, 1991 to December 31, 2003. The two smaller time sequences were used to assist in identifying and evaluating sh orter-term trends (fiv e to six years). Within the time sequences, each analyte needed to have a minimum of 10 data points in order for any statistics to be pe rformed. In addition to the minimu m number of 10 data points, it was arbitrarily decided that for Sequence A at least three data points from Sequence B and at least three data points from Sequence C needed to be present. If Sequence A lacked this additional criterion, then no analyses were performed on the sequen ce. As an example, suppose a spring had 15 data points, 12 in Sequence C and three in Sequence B. An analysis for trend was conducted for Sequence A, and C, but not B. If a spring only has 14 data points, 12 in Segment C and two in Segment B, then no analyses was performed for Sequence A nor Sequence B. However, the statistical analysis was conducted for Sequence C. A question arises, are only three data points sufficient to represent the time Sequence B or C within Sequence A? It certainly is not desirable and is an example of messy data. This situation was considered to be sufficient for trend analyses because this study represented the first statewide analyses for trends. Fortunate ly, this was not a common situa tion and, hopefully in the future, available data will be less messy. Data Used for Analyses and Explanation of Appendices All data presented in this report represent a collaborative effort among the five water management districts, the U.S. Geological Survey and the Florida Geological Survey for spring data, plus Alachua, Palm Beach, Broward, Miami-Dade Lee, and Collier Counties for well data. This is significant since each sampling agency has its own agenda resulting in different reasons for the collection of a particular analyte. Resultant data for both spri ngs and wells can be found in Appendix H. The appendix contains the actual concentrations for the analytes measured. The state is broken down into three regions, Northwest, Central, and South Florida. Within each regional folder the data are placed in their respective WMD. Missing data were noted with an asterisk. In the folder, the results of the MK analyses along with the corresponding n (number of data points) and the Sen Slope (SS) for each spring and well (to be discussed later) can also be found. The format is similar to that within the data folder. Finally, plus/minus charts (to be discussed late r) are also included.

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FLORIDA GEOLOGICAL SURVEY 30 The data in the statistical analysis folder are temporal data. A numerical value of -9999 was included to maintain the order of the spread sheet. A value of -9999 can either mean that data are missing or it can mean th at there are an insufficient number of samples to perform the statistical analyses (procedures to be discussed later). The remaining data were placed in tables. The tables contain the following information: (1) the identification (ID) that names the spring (or well), (2) its location in latitude and longitude, (3) the time sequence, (4) the dates fo r which samples were obtained, (5) a p-value for significant increase, (6) a p-value for significant d ecrease, (6) the total number of samples within the sequence, (7) the calculated SSs, and (8) the trend results. With regards to the results, the tables indicate whether there was a significant increase (UP), decrease (DOWN), or no evidence of trend. Throughout this report an upward trend will be designated with either an up arrow () or a plus sign (+). A downward trend will either be designated with a down arrow () or a negative sign (-). INFORMATION GOALS AND DATA ANALYSIS PROTOCOLS Information Introduction The purpose of data analyses was to document water-quality trends in Floridas springs and wells for the period 1991 2003. Prior to evaluation, a list of information goals was developed. The goals were then turned into specific questions for which statistical procedures could be used in an attempt to answer them. The questions are listed be low and are followed by a discussion of the statistical procedures used in this report. A more de tailed discussion of all statistical procedures used in this report can be found in Appendi x E.1 and E2. Minitab Release 14 (Minitab, 2003) and S-PLUS 6.2 Professional Edition (S-PLUS, 2003) were used for all analyses. The six questions were: 1. What were the statistical distribu tions for each of the sampled analytes? 2. For Sequence A (the longest time sequence) for each analyte, and for each spring or well, was season ality present? 3. For each sequence, for each analyte, and for each spring or well, were linear time series trends present? 4. If trends were present, what were their slopes? 5. For springs or wells with detectable tr ends, were they spatially related? 6. If evidence was found to indicate that the degrading trends were man-induced, what are plausible solutions and recommendations? Overview of Statistical Analyses Procedures Descriptive Statistics Descriptive statistics were produced for each analyte at each spring and well (station) for the longest time sequence. The descriptions can be found in Appendix I. For each sampled station for Sequence A, the tables list the analyte (or indicator), the measurement unit, the

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BULLETIN NO. 69 31 number of samples collected, the number of sa mples with concentrations below the laboratory detection level (BDL), the minimum value, the first, se cond and third quartiles, and the maximum value. The first, second and third quartiles (Q1, Q2, and Q3) correspond to the 25th, 50th (median), and 75th percentile respectively. An exampl e of the descriptive statistics is presented in Table 6. For a given analyte, the reported minimum concentration value in the table often reflected the minimum detection level reported by the analyt ical laboratory. Table 6. Example of Descriptive Statistics Table (Sequence A; January, 1991 December, 2003) Analyte Meas. Unit Num. Samp. Num. BDLs Min Value Q1 Value Median Value Q3 Value Max. Value NO3 mg/L 30 7 0.05 0.09 1.00 2.00 10.30 PO4 mg/L 29 4 0.05 0.10 0.10 0.15 1.30 Kruskal-Wallis, Mann-Whitney, and Wilcoxon Rank Sum Tests Seasonality can be thought of as periodic fluctuations or cycles. As an example, Figure 11 displays monthly water temperatures for an imaginary well during the 1992 calendar year. Not surprisingly the temperature is highest during the summer and lowest during the winter months, indicating that for temperatur e there exists a one year cycle. DateTemp (Deg C) 1/1/1993 11/1/1992 9/1/1992 7/1/1992 5/1/1992 3/1/1992 1/1/1992 22.6 22.5 22.4 22.3 22.2 22.1 22.0 21.9 Monthly Water Temperatures(Calendar Year 1992) Figure 11. Monthly water temperatures plotted over the 1992 calendar year for an imaginary well. Cycles are not restricted to calendar years. They can occur over vi rtually any length of time. Figure 12 displays an example of a cycle longer than one year. In the example, the concentration of an imaginary analyte has a six year cycle or season. Depending on the variable of interest, it may or may not have been influenced by cycles whose fre quencies are longer than 13 years; Sequence A was 13 years in length (1991). It is difficult to make that

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FLORIDA GEOLOGICAL SURVEY 32 determination of the cycles in fluence on the analyte. With this in mind, the authors were concerned with the influence of shorter term cycles on Sequence A. Since ground-water samples were collected on a quarterly and monthly basis wh ile springs were sampled either on a quarterly or quasi-quarterly fashion, it was decided to de termine if cycles in those frequencies were present in the data. Figure 12. Example illustration of seasonality with a six-year cycle. For each spring or well for Sequence A, the pr esence of seasonality for each sampled analyte was determined using a Kruskal-Wallis (K W) test (Hollander and Wolfe, 1973; Gilbert, 1987). Quarterly and monthly seas onality tests were conducted be cause stations were generally sampled quarterly and occasionally monthly. It should be noted that m onthly seasonality tests could only be conducted if samples were collected on a monthly or quasi-monthly basis. For the most part, monthly samples were only collected fo r 24 of the 46 wells and only for field analytes. On the other hand, quarterly samples were obtain ed on the remaining wells and quasi-quarterly samples were collected on most of the springs The quasi-quarterly sampling by the WMDs and the arbitrary seasonal breakdown was as follows: (1) December February, (2) March May, (3) June August, and (4) September November. It should be noted that as we conducted the analyses for trends, we found that, based on the four arbitrary seasons, most analytes did not display significant seasonality. We recognize that in the future, with the acquisition of additional data and with additional trend analyses, a better breakdown may be discovered. Nevertheless, for this analysis exercise, the KW test was used to compare the distribution of two or more populations (seasons) by indirectly comparing their median values during each season as defined by this study. If we had defined only two seasons, the KW test is equivalent to a Mann-Whitney (MW) test (Conover, 1999). Both tests are discusse d in greater detail in A ppendix E. It should also be noted that the results of the MW test are identical to another very similar test; the Wilcoxon rank sum test (WT) (Conover, 1999). The WT test was occasionally used during this

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BULLETIN NO. 69 33 study because some of the statistical software used included the WT test rather than the MW test. Conover (1999) discusses the WT test in detail. Resu lts of the WT test are identical with those of the MW test. Consider a situation in which one wants to determine if two populations have the same statistical distributions for a gi ven season and samples are theref ore obtained for each season. For the MW test, the null hypothesis is that the median of the tw o populations are the same while the alternate hypothesis is that they are not. The two samples are combined into a single ordered sample from smallest to highest Each observation is then a ssigned a rank with out regard to which sample it originally came from. The sum of the ranks assigned to those values from one of the populations is then generated. If the rank sum of the corres ponding population is very small (or very large), there is an indication th at the values from one population tends to be smaller (or larger) than the values from the other. If so, the di stributions of the two populations are not equal. If the rank sums of the two populations are not equa l, neither are their medians. Returning to the KW test, it compares the di stribution of more than two populations (e.g., seasons). For this report, each test was tw o-sided. The null hypothesi s is that the median concentration of an analyte sampled in any se ason is equal to the median of the remaining seasons. The alternate hypothesis is that the median concentrati on for at least one season is not equal to the others. Under the latter scenario, it is assumed that seasonality does exist. For quarterly data, tests were conduc ted assuming that each quarter was a season. For monthly data sets, tests were conducted assuming that each m onth was a season. The level of significance was preset to = 0.05. For example, 38 temperature samples were collected at Weeki Wachee Main Spring for time Sequence A. However, data were not avai lable for the period 1991 through most of 1993. Data were available for the 1993-2001 time frame. All samples were sampled on a quarterly basis; nine in each of seasons (1), (2), and (4), plus ten in season (3). The KW test compared the median values for each of the four seasons and, based on the test, it was concluded that the median of at least one season did not equal the other medians. Thus, it was concluded that quarterly seasonality does exist for the spring with respect to temperature. Since monthly data were not available, no conclusion could be made regarding monthly seas onality. Results for these analyses are f ound in Appendix J. Deseasonalized Data If seasonal cycles were present in the data, the data were deseasonalized using a method presented by Intelligent Decision Technologies ( 1998). Although most measurements of central tendency used in this report pertain to the me dians, means were used (Sen, 1968) in the deseasonalization transformation equation (Intelligent Decisions Technologies, 1998). The Sen method subtracts the mean of the correspondi ng season from each datum and then adds the overall average (mean) of the se quence back to the original datum. For example, suppose 10 years of quarterly data were collected at a site for chloride. Suppose the overall mean of the data for the 10 year period was 1.0 unit while the mean of the winter quarter was 0.2 mg/L. Now suppose a concentration for a particular winter quarter sample was 1.2 mg/L. In mg/L, the corresponding transformed, des easonalized datum becomes:

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FLORIDA GEOLOGICAL SURVEY 34 x = (original) [seasonal (w inter) mean] + (overall mean) = (transformed x ) x = 1.2 mg/L 0.2 mg/L + 1.0 mg/L = 2.0 mg/L. Mann-Kendall Test Gilbert (1987) stated that th e Mann-Kendall (MK) test can be viewed as a nonparametric test for zero slope of th e linear regression of time-ordered da ta versus time. Given that it is a nonparametric technique, it does not depend on an assumption of a particular underlying distribution. The test identifies correlations in data through temporally ranking the data and then determining the number of times the concentratio n goes up or down relative to the previous time step. It only uses the relative magnitudes of th e data rather than their measured values. Data reported as trace or below the mini mum detection level (MDL) were used by assigning a common value that was smaller than, or equal to, the smallest measured value in the data set. For this report, below detection leve l (BDL), was assigned an arbitrary value equal to the detection le vel (DL). Once the seasonality tests were completed (results found in Appendix J), each analyte was tested for a linear trend using the MK test ( = 0.05) for each time sequence. A macro program was used for the analysis while working within Minitab [Appendix E.1)]. However, if data were insufficient (n < 10), the MK test wa s not conducted. For this exercise, we always used a one-sided test. The reason was that we had a preconceived idea as to whether or not a downward (or upward) trend was an indication th at conditions were gettin g worse (or better). The results of the MK tests are found in Appendix K. Seasonal Kendall Test A common test used in the analyses of time series is the Seasonal Kendall (SK) test (Gilbert, 1987). It is an adoption of the MK test, and can be used if there is seasonality in the data. The SK test is the technique of choice. Unfortunately, it has a set of requirements that were not obtainable. Miller et al. (2004) mentioned that the test requires that the percentage of censored data (e.g. data reported as BDL) be no more than about five percent. In addition, Miller stated that there should only be one censoring level. This latter requirement was not obtainable because our data were obtained from ag encies operating independently of each other. The agencies used multiple laboratories with multiple detection levels, which amounted to multiple censoring levels. Thus, the SK test was not used in this investigation. In the future, as better and more consistent data are obtaine d, the SK test is th e recommended test. Sen Slope If a trend was found to exist for either nonseasonal or seasonal data, its corresponding slope was determined using a Sen Slope (SS) estimator (Sen, 1968; and Gilbert, 1987). The estimator measured the median difference betw een successive concentr ation observations over the time series. The SS was used only to measure the magnitude of the slope It was not used as a hypothesis test. Results are found in Appendix K.

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BULLETIN NO. 69 35 Sign Test For each analyte exhibiting a trend, a map showing the location of the corresponding station was created. In additi on to statistical evaluations, visual estimates were made as to whether clusters of corresponding up ward or downward trends existe d. Associations with depth, land use, and other relationships were evaluated. The last statistical proc edure used was the sign test (Sullivan, 2004). The sign test is a relatively simple procedure to conduct. It was used to determine if a significant number of stations demonstrated upward or downward trends over a geographical region. Note that on e spring in the SWFWMD was not used in the analyses. The reason will be disc ussed later. As an example, suppose during Sequence A, 29 of the 57 springs displayed an upward trend for nitrate. Can it be conc luded that there exists an upward statewide trend? What if 40 (or 45) of the springs demonstrated upward trends? If one thinks of the causes of trends in individual stations as be ing random processes, we could expect about half of the springs to have upward trends, while about half should have downward trends. On the other hand, if a large proportion of the springs had upward trends, we might be suspicious that one or more phenomena were affecting springs and causing the upward trends over a region. Finally, if an extremely large proportion of the springs demons trated upward trends, we would become even more confident that the phenomena were affecting the upward concentr ations over a region. For the sign test, one assigns a (+) value if there is an upward trend and a (-) value if there is a downward trend. Sulliv an (2004) stated that zeros add nothing to the test and therefore should be eliminated from further analysis. Th us, all springs demonstrating no trend were assigned a value of zero (0) and were eliminated from further analyses The test simply compares the proportion of + values to the values. For this exercise, was preset to 0.05 for the level of significance for these evaluations. Caveats and Assumptions It should be noted that this study was not set up as a designed experiment. We took existing data and attempted to evaluate them. As a consequence, there were many less-thanperfect situations that we needed to address in order to conduct the statistical analyses related to this project. Whenever one takes existing data which were originally collected with a variety of goals in mind and attempts to evaluate them with a new set of objectives, problems should be expected. For example, R.A Fisher, a sta tistician sometimes referred to as the Father of Modern Statistics (Sullivan, 2004), once stated, To call in the statistic ian after the experiment is done may be no more than asking him to pe rform a postmortem examination: he may be able to say what the experiment died of. This quote is appropriate for our study. We faced many unpleasant situations with rega rd to the data analyses. One of the major sources of problems pertai ned to the assumptions of the statistical procedures (see Appendix E). Generally these te sts assumptions are: (1) the measurements are mutually independent, (2) the observations ar e random, (3) the populations are continuous, and (4) the scales or measurements are at least ordina l. For the sign test, the assumptions are slightly

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FLORIDA GEOLOGICAL SURVEY 36 different: (1) the stations are mutually independent, (2) the measurement scale is at least ordinal, and (3) if the probable outcome of a sign is (+) or (-), for one station, the same is true for all other stations. With the exception of the indepe ndence issue, the assumptions were valid. The issue of dependency will be a ddressed during the discussion of the results of the study. RESULTS The trend results of every spring and well for each analyte can be found in Appendix K. What follows is a set of examples from selected springs and wells. Our purpose is to give the reader a generalized idea about the behavior of analytes duri ng the study period. Although some discussion regarding the causes of trends at an individual spring will be discussed, the emphasis of this report is on regional and statewide trends A discussion regarding the possible sources of the analytes and the most probably causes of trends can be found in Upchurch (1992) and Appendix B2. The trend results are divided in to both springs and wells by water management district. There were no springs analyzed in the SFWMD. Thus springs were geographically divided into the NWFWMD, SR WMD, SJRWMD, and SWFWMD. A note is needed regarding the relationship between time-series figures and Sequences. If sufficient data were available, time series analyses were generated for each Seque nces A, B, and C. However, if data were missing for the front or back end of the Sequence, the corresponding figures still cover the entire sequence. As an example, the first series di scussed is for magnesium in Wakulla Spring during Sequence A (1991-2003). Unfortunately, no data exis ts for the last two years of the sequence. Nevertheless, the figure displays th e entire sequence. This is true for all time series discussed. Springs Northwest Florida Water Management District In the NWFWMD, only Wakulla Spring (Figure 13) had sufficient data for analyses for this study. Wakulla was sampled through a piece of tubing placed into a major conduit of the spring. Thus, the samples are considered spring-w ater samples. However, for years, the FDEP has, for administrative purposes, considered the tubing to be a well (Well 67 in the Temporal Variability Network). Since FDEP considers the station to be a we ll and the fact that the tubing taps a spring vent, the station for this report was analyzed both as a spring and a well. Stage data were collected at the spring vent, and st age was used in lieu of water levels. Rock and Saline Analytes Nutrients, and Flow Rock-matrix analytes included cations such as calcium and magnesium. Wakulla Spring shows an increase in dissolv ed magnesium over time Seque nce A (1991-2003). Increases in magnesium and specific conductance (SC) are illu strated in Figure 14. The time series for magnesium at Wakulla, like many analytes, show ed inconsistent sampling over the period of record. In this case the time period from 1994 to 2000 contai ned only one point. For the given data, the MK

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BULLETIN NO. 69 37 Figure 13. Location of Wakulla Spring within the NWFWMD. test confirmed an increasing tr end (p < 0.05). For almost every time-series figure, the median value of the second half of the sequence was compared to median of the first half, using the Wilcoxon rank sum test (WT). This enabled us to not only determine the slope of the trend, but to also better evaluate magnitude of change during the time series. There was a significant change over the period of record (p < 0.05). Whet her by analysis of trends, or comparison of two halves of the time sequence, the latter half of the st udy revealed elevated values of dissolved magnesium. The missing data from the intervening years in the magnesium time series (Figure 14, top) appear to be accounted for in the time series for SC (Figure 14, bottom). Wakulla Spring showed a clear increase in SC over time. The probable causes for the increases in magnesium and SC, will be discussed later on a dist rictwide and statewid e perspective. Figure 15 (top) displays a trend for nitrate-ni trite concentrations in Wakulla Spring for the 1991-2003 time frame. The time series show s noticeable data gaps from 1995 to 2000 and again during 2001-2003. In the Wakulla Basin, Chelet te et al. (2002) indi cated that there are several significant sources of nutri ents. These include effluent from a large spray field, fertilizer application, and numerous onsite waste disposal treatment sites (OSTDS) within the basin, and up-gradient of the spring. Fort unately, it appears, since 1991, th e concentration of nitrate has significantly decreased. Nitrate in the form of dissolved nitr ate-nitrite declined (Figure 15, top).

BULLETIN NO. 69 39 Figure 15 Decreasing nitrates and water levels at Wakulla Spring. Dissolved nitrate (top) and water levels (bottom) had significant trends. Tests (p = 0.05) included MK and WT. WT compare medians of the first and second halves of the study. (1.0 m = 3.3 ft)

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FLORIDA GEOLOGICAL SURVEY 40 MK and WT tests indicate that whether by trend analysis or comparison of the first and second half of the time sequences, concentrations of ni trogen decreased. Loper et al. (2005) suggested that the decreasing nitrate concentr ations were due to lowered con centrations of effluent from a large spray field located within 16 km (10 mi) of the spring. Figure 15 (bottom) illustrates a significant drop in stage level Suwannee River Water Ma nagement District Figure 16 displays the locations of the 15 sp rings located in the Suwannee River Water Management District (SRWMD) used in this report. The spring names and the abbreviations are found in Table 7. Figure 16. Location of springs within the SRWMD.

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BULLETIN NO. 69 41 Table 7. Suwannee River Water Management District Spring Names and Abbreviations. Spring Abbreviation Spring Abbreviation Alapaha Rise ALR Poe Spring POE Gilchrist Blue Spring GIL Blue Ruth/Little Sulfur Springs RLS Fanning Spring FAN Rock Bluff Spring RKB Hart Spring HAR Royal Spring ROY Hornsby Spring HOR Suwannee Blue Spring SBL Lafayette Blue Spring LBS Telford Spring TEL Little River Spring LRS Troy Spring TRY Manatee Spring MAN Many of the springs are located along the Su wannee River, along a se ction of the river which is roughly perpendicular to the coast, at least in its lower stretch. Numerous trends were noted along an approximate south to north, or lower to upper, river direction. (Specific results are found in Appendix K). Rock-Matrix and Saline Analytes Calcium, magnesium, and sodium increased strongly in the SRWMD over Sequence A. Increases were particularly str ong in the latter half of the st udy (Sequence C). Increasing trends were dominant for several analytes. Magnesium and sodium had significant increases in eight of 14 springs with no decreases. Calcium increased in nine springs. Examples of increases in the rock indicators are shown in Fi gures 17-20. Figures 17 and 18 illustrate tr ends in calcium for four springs over Sequence A while Figures 19 and 20 demonstrat e patterns for magnesium for four springs over Sequence A or C, depending on the spring. Note that for many of the time-series figures that compared two stations, the vertical scales do not coincide. By keep ing the vertical scales constant occasionally the variability of one graph became so small that you could not see it In the end, we decide d it was better to use inconsistent vertical and to em phasize variability over time. Changes in calcium in springs for the lower Suwannee River are similar to changes in springs farther north. Fanning Spring (FAN) and G ilchrist Blue Spring (GIL Blue) illustrate two of the nine springs that exhibite d an increase in calcium (Figure 17). In addition to calcium, FAN showed significant increases in other rock-mat rix and saline indicators including alkalinity, chloride, potassium, magnesium, sodium, and speci fic conductance. The time series plot in Figure 17 shows a gradual increase in calcium from 60 mg/L in 1995 to approximately 80 mg/L in 2003; the gradual increase had a low varian ce around the best fit line. When data for sequences B and C were compared, Sequence C da ta had clearly higher medians (WT test pvalue, <0.0001, illustrate d by box plots in inse t figure in bottom corner). Like FAN, for Sequence A, calcium concentrations in GIL Blue increased. The initial concentration was about 50 mg/L and ended with 65 mg/L; both springs in creased in concentration by approximately 20 mg/L. GIL Blue also had many other analytes with upward trends that mi rrored FAN: alkalinity, chloride, magnesium, sodium, and specific conductance. Springs farther north (Figure 18) had similar looking trends to those springs located farther south (Figure 17), although the overall trends in other analytes were different. Suwannee Blue Spring (SBL) and Troy Spring (TRY) together had increases in only

FLORIDA GEOLOGICAL SURVEY 46 calcium, magnesium and sodium. Unlike FAN a nd GIL Blue, SBL and TRY exhibited no linked trends in alkalinity, chloride, pota ssium, or specific conductance. Toward the south, Manatee (MAN) and Hart (HAR) (Figure 19) began the time series with approximately four mg/L of magnesium; by the conclusion of th e series, they were at six to seven mg/L. Further north, Poe Spring (Poe) (Figure 20) began at about four mg/L in 1998 and rose to about 10 mg/L in late 2002. Lafayette Blue Springs (LBS) (Figure 20)( began at about eight mg/L in 1998 and rose to about 14 mg/L in 2001. Flow The SRWMD consistently collected flow or di scharge data at specific spring vents during the same day that they collected water sample s from their springs. However, the SRWMD did not begin collecting discharge da ta until the 1997-1998 time frame. During Sequence C, for the SRWMD, flow ra tes decreased significa ntly in 12 of 16 springs. There was not an increase in flow ra te in any of the spri ngs during the same time sequence. In addition, the degree of decrease in flow was sometimes severe. Figures 21-24 illustrate the trends for eight springs starting at the lower end of the Suwannee River and moving inland and northward. Springs at the lowest end of the Suwannee River included Fanning (FAN) and Hart (HAR) Springs (Figure 21). Both springs show substa ntial drops in flow levels. By the end of the period of record, flow was reduced to approximately half the levels seen at the beginning of the time series. FANs highest recorded flows were near 120 cubic feet per second (cfs), but ended near 50 cfs. HARs highest record ed flow was approximately 90 cfs and fell to near 40 cfs at the end fo the time series. Upstream from these springs are Rock Bluff (RKB) on the Suwannee and Hornsby (HOR) Springs on the Santa Fe River (Figure 22). Both displayed even sharper declines in flow. Rock Bluff went from a high of 50 cfs to under 20; flow was reduced to zero cfs briefly in 2001. Hornsby showed an even stronger decline: over 200 cfs was m easured in 1998 and the flow reduced to zero cfs during a period starting in early 2000. This was followed by a small recovery of flow rate in 2003. Poe Spring, on the Santa Fe River, and Litt le River Sulfur Spring (LRS) on the middle Suwannee region had strong declines in flow rate (Figure 23 (Sequence A; but mostly C)). Poe Spring recorded discharges of 60 to 80 cfs near the beginning of the time series but declined to near 20 cfs by the end. LRS began the time series with a flow rate near 90 cfs and ended near 20. Decline in flow at LRS closely followed a regr ession line fit to the da te (Figure 23, bottom). Troy (TRY) and Telford (TEL) Springs both ha d downward trends in flow. Though flow at Troy was approximately three times higher than Telford (Figure 24; Se quence A, but mostly C)), there was a slight increase in flow in mid-1998 followed by a decrease for both springs in early 2000, and then another slight increase in fl ow occurred in late 20 01. Overall, both springs seem to show that flow was reduced by at least half, with LRS indicating a reduction in flow by a third at the end of the time series.

BULLETIN NO. 69 49 Figu re 23. Decreasing flow at Poe and Little River Springs. Poe (top) and Little River Springs (botto m) had significant decreases in flow. Tests (p < 0.05) include d MK for trend, WT, plus an SS calculation on rate of change. For both Poe and Little River flow reduced to about one third by the end of the series. Beginning and ending sampling dates are not the same. (One cfs = 0.028 cms) Little River Spring Sequence A (19912003) Poe Spring Sequence A (19912003)

BULLETIN NO. 69 51 Nutrient Analytes For the study period, nutrien ts in the SRWMD had more complex patterns than the patterns of either the salinity indicators or fl ow. While some nutrient trends were very strong, others were not as clear. During Sequence A, o f the 15 springs in the SRWMD, TKN increased significantly in nine spri ngs (with no decrea sing trends). Nitrate appear ed to decrease (downward trend in six springs, while it increased in thre e springs). At the same time, other nutrients phosphorus and phosphate specificallyappeared to increase. For phosphorus, there were five springs with increasing trends and only one sp ring indicating a decreas e; for phosphate there were four springs with incr easing trends and only one spri ng with a decreasing trend. The FDEP has a maximum nitrate standard of 10 mg/L for groundwater and Class I surface water before considering th e water impaired. Both water standards are directed toward maintaining drinking water quality (Florida De partment of Environmen tal Protection, 1994). Currently, there is not a numeric standard that is directed toward changes and concentrations of biota in surface water. However, FDEP has es tablished a non-legal threshold for nitrate and phosphorus for surface water (Florida Depart ment of Environmental Protection, 2004) The thresholds were based on a stat ewide evaluation of ch lorophyll concentrati ons in lakes. The groundwater-surface water relation al assessment (SRA) limit is 0.45 mg/L for nitrate. Groundwater nitrate concentrations exceeding the 0.45 mg/L limit suggest that there is a potential for adverse affects on aquatic organism s in the spring runs. Technically, the threshold level applies only to surface water and there is a need to establish a groundwater to surface water interaction for the threshold to be relevant. Since springs represent an interaction between groundwater and surface water, we used the threshold level for comparative purposes. Figures 25 and 26 represent examples of changes in nutrients in spri ngs of the SRWMD. Figure 25 is an example of a decreasing nitrate trend. Nitr ate significantly decreased from 1998-2003 for Poe Spring. For comparative purposes the SRA was chosen as a fixed reference a nd is the gray line in Figure 25. Poe Spring exceeded the SRA recomme ndations prior to 1999, but then declined to levels below the SRA. Possible reasons for the d ecline in nitrate in the Suwannee Basin will be discussed later. While nitrate often decreased in the SRWMD, TKN rose significantly. Phosphorus also exhibited some increasing concentrations. To tal phosphorus at Poe Spring (Figure 26) almost doubled from 1999 to 2003. Phosphorus and phosphate both increased at several springs. An even greater number of upward trends, however, we re seen for TKN. Figure 26 (bottom) shows an increase in TKN at Lafayette Blue Spring ov er the study period. The plot also illustrates some of the differences between nutrient and sali ne trends. While saline and rock-matrix analyte plots give evidence of clear increases, trend lin es for nutrient plots were sometimes less well defined and potentially not as strong. Figure 26 shows a sign ificant upward trend for total phosphorus (MK test, p < 0.05) though the p-valu e of 0.0443 does not indicate such a strong increasing trend; data for the first and second ha lf of the time sequen ce were not significantly different (WT p-value = 0.3633). The potential cau ses of nutrient and ot her trends will be discussed later.

FLORIDA GEOLOGICAL SURVEY 54 St. Johns River Water Management District The springs located in the St. Johns River Water Management District (SJRWMD) and used in this report are found in Figure 27. Spring names and abbreviations are found in Table 8. Figure 27. Location of Springs within the SJRWMD. 10 20 40 Miles , , I I , , , I I 15 30 60 Km Legend --wrTlcUines selection Springs SFW M O SJRWMD SRWMD SWFWMD 10 20 40 Miles , , I I , , , I I 15 JO 60 Km Legend --wlT1cUines selection Springs SFW MO S JR WMD SRWMD SWFWMD

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BULLETIN NO. 69 55Table 8. St. Johns River Water Management District Spring Names and Abbreviations Spring Abbreviation Spring Abbreviation Alexander Spring Alexander Salt Springs Salt Apopka Spring Apopka Sa nlando Springs Sanlando Fern Hammock Springs Fern Silver Glen Springs Silver G Juniper Springs Juniper Starbuck Spring Starbuck Miami Spring Miami Sweetwater Spring Sweetwater Palm Spring Palm Volusia Blue Spring Vol Blue Ponce De Leon Spring PDL Wekiwa Spring Wekiwa Rock Spring Rock Calcium, strontium, fluoride, and pH incr eased in a significant number of springs over time Sequence A, while phosphate leve ls decreased. With respect to individual springs, Miami, Palm, Sanlando, and Wekiwa Springs had at leas t eight analytes with increasing trends over Sequence A, while Volusia Blue Spring (Vol Blue) and Sweetwater Spring decreased in at least eight analytes over the same time sequence. Alex ander, Salt, and Silver Glen (Silver G) Springs each had six or fewer analytes showing any trend (positive or negative). Sequence B had no districtwide trends. During Sequence C fluoride and pH incr eased in a large number of springs while flow decreased at many locations. Rock-Matrix and Saline Analytes Increasing trends were associated with the following rock-matrix analytes: strontium, calcium, pH and fluoride increased over Sequence A. Nine springs had significant increases in calcium and pH while one spring had a decreasing trend for theses analytes. Both fluoride and strontium increased in 10 springs. Strontium d ecreased in one, whereas fluoride decreased in none. No trends were observed in Sequence B. Within Sequence C, upward trends were observed for fluoride and pH, while flow decrea sed. Thus, major changes for the SJRWMD, like other districts, occurred dur ing 1998 to 2003 (Sequence C). Figures 28-30 depict increases in two rock-matrix analytes for three springs in Seminole and Orange Counties. Not depicted are Starbuck, Rock, and Apopka, which showed the same pattern. Alkalinity and strontiu m suggest changing chemistries. Both analytes increased in Palm, Sanlando, and Wekiwa Springs. All plots show trends closely fitting an increasing best-fit line. Starting at about 116 mg/L for alkalinit y, Palm Springs increases to about 126 mg/L. Sanlando Springs begins at about 130 mg/L and increases to approximately 150 mg/L. Strontium at Sanlando Springs began around 60 g/L and ended over 90 with little variation in the upward trend. Wekiwa Spring st arted at a higher level (near 100 g/L) and ended the time series at about 140 g/L. Wekiwa Spring is also unique in showing an a pparently quick increase in concentration between 1993 a nd 1995. Palm Springs differed from the other two springs in having strontium concentrations at the start of the study three to four times higher than the other two springs.

BULLETIN NO. 69 59 Nutrient Analytes For the study period, there were fewer nutrien ts trends in the SJRWMD than in other WMDs. For example, both phosphorus and TKN dem onstrated few to no changes (no increases or decreases for phosphorus, no increases and tw o decreases for TKN). Nitrate showed no clear trend direction. For example, in the seven springs showing trends for nitrate, three increased and four decreased. With respect to nutrients, only phosphate showed consistent trends across the district. Eleven springs decreased in phosphate while no springs increased. Figure 31 shows two phosphate trends, which also are cons idered to be Rock-matrix analytes. Phosphate levels for both Palm and St arbuck Springs fell by nearly half of the initial concentrations. Phosphate at Palm Springs (top figure) began the time se ries at approximately 0.15 mg/L and dropped to about 0.09 in 2002. Values from the end of the time series, 2002 to 2003, suggest a rise in concentrat ions. Starbuck levels began n ear 0.17 mg/L and fell to about 0.12 mg/L. Similar to Palm Springs, Starbuck appears to record a rise in concentrations near the end of the time series in 2003. Southwest Florida Water Management District Figure 32 shows the locations of the springs in the SWFWMD. Table 9 displays the corresponding spring abbreviations. Note that after our analyses, the SWFWMD notif ied the authors and told us that they now question the validity of using Boyette Spring da ta. They now believe it receives a significant portion of its water from a nearby sinkhole (< 1 k ilometer away) and much of the receiving water is dairy waste (Morrison, 2000). Since the indi vidual spring analyses were already completed, we decided to keep the spring in the analyses However, because of the point-source dairy contamination, Boyette Spring data were removed from districtwide and statewide analyses. Also, the SWFWMD was the only WMD to analy ze for bicarbonate, rather than alkalinity. The SWFWMD springs had strong trends in rock-matrix, salin e and nutrient indicators. Similar to the SRWMD, rock-matrix and saline indicators rose significantly. Unlike the SRWMD, nutrient indicators showed different types of trends. Differences in behavior of nutrients between the SRWMD and SWFWMD sugge st regional differences exist between these two areas. Similarities in rock-matrix and saline trends between the SRWMD and SWFWMD suggest these trends extend beyond district boundaries. Some sp rings showed more changing chemistries than others. Betty Jay, Boyette, an d Tarpon Hole Springs had many analytes with increasing trends. Buckhorn Main and Hidden Rive r No. 2 Spring had a nu mber of decreasing trends. Those showing no trends among the an alytes studied during time Sequence B included Boat, Bobhill, Rainbow Swamp N o. 3, and Wilson Head Springs. Rock-Matrix and Saline Analytes Strong increases in both rock-m atrix and saline analytes were evident in springs in the SWFWMD during time Sequence A. Analytes with increasing trends incl ude bicarbonate,

FLORIDA GEOLOGICAL SURVEY 62Table 9. Southwest Florida Water Managemen t District Spring Names and Abbreviations Spring Abbreviation Spring Abbreviation Betty Jay Spring Betty Jay Hunters Spring Hunters Boat Spring Boat Lithia Main Spring Lithia Main Bobhill Spring Bobhill Magnolia Spring Magnolia Boyette Spring Boyette Pump House Spring Pump House Bubbling Spring Bubbling Rainbow No. 1 Spring Rainbow No. 1 Buckhorn Main Spring Buckhorn Main Rainbow No. 4 Spring Rainbow No. 4 Catfish Spring Catfish Rainbow No. 6 Spring Rainbow No. 6 Chassahowitzka No. 1 Spring Chassahowitzka No. 1 Rainbow Bridge Seep Rainbow Bridge Seep Chassahowitzka Main Spring Chassahowitzka Main Rainbow Swamp Spring No. 3 Rainbow Swamp No. 3 Hidden River Head Spring Hidden River Head Salt Spring Salt Hidden River No. 2 Spring Hidden River No. 2 Tarpon Hole Spring Tarpon Hole Homosassa No. 1 Spring Homosassa No. 1 Trotter Main Spring Trotter Main Homosassa No. 2 Spring Homosassa No. 2 Weeki Wachee Main Spring Weeki Wachee Main Homosassa No. 3 Spring Homosassa No. 3 Wilson Head Spring Wilson Head calcium, chloride, potassium, magnesium, sodi um, conductivity, sulfate, strontium, and total dissolved solids. Of these, incr eases strongly attributable to ro ck chemistries were bicarbonate and strontium. Regarding salin ity, rises in sodium, chloride, and total dissolved solids were observed. Analytes in common to both groups included calcium, potassium, magnesium, specific conductance, and sulfate (which showed strong increases). Similar to other districts, Sequence B had very few trends. The majority of the infl uence for these increases occurred during time Sequence C. Chloride increased in 18 springs. Figures 3335 depict the chloride trends from several springs in the northern SWFW MD along the Gulf Coast. Springs occur from north to south along the Gulf Coast. Figure 33 includes two springs from southern Marion County, one of the north ernmost counties in SWFWMD. These springs, Rainbow No. 6 and Bubbling Springs, increased in chloride concentrati ons, both springs show a steady increase during the years of Sequence A. Both springs began with 3.0-4.0 mg/L of chloride and ended the time series with approximately 5.0-6.0 mg/L. For a couple of springs just to the south in Citrus County, the increase in chloride was more dramatic (Figure 34). Hunt ers Spring (top) began the time se ries with approximately 50 mg/L of chloride. Values rose quickly at one point, more than doubling, and then declined. Trotter Main (bottom) showed a similar pattern, though with shar per changes. Tr otter Main had values of approximately 50 mg/L near the start, as did Hunters, but then increased to nearly 250

FLORIDA GEOLOGICAL SURVEY 66 mg/L at one pointa five-fold increase. Figure 35 depicts chloride concentrations at Weeki Wachee and Bobhill Springs. Weeki Wachee began th e time series with only about 6.0 mg/L of chloride and ended with a concentration of a bout 8.0 mg/L. Bobhill Spring began about 5.0 mg/L and ended with about a 9.0 mg /L chloride concentration. Flow Flow data were available for only three gaging stations within the SWFWMD. While there were inadequate data to make statistical conclusions for the SWFWMD, data from the three` stations suggested possible declines simila r to the SRWMD. Homosassa No. 1 flow levels declined for the years 1996-2003 (Figure 36). Longer-term trends are depicted in Figure 37, which further illustrates declines in flow. Si nce the 1960s, average y early flow for Rainbow Springs has declined (dark gray line indicates a timeline for Sequence A). WT tests between the first and second half of the data series show a difference between the two data series. However, for data representing time Sequence A, results do not indicate a significant difference. This suggests that trends on the scale of this study (i.e ., 13 years) may sometimes be missed in spite of being part of a larger change (e.g. 40 years of data). Long-term flow in Weeki Wachee Springs flow data (Figure 37, bottom) has an equally interesting pattern. Although no regression is disp layed, flow data going back to 1904 displays a rise until the 1960s, followed by a de cline until the present. Gray lines illustrate th e time line for Sequence A and that for post-1960. The range in fl ow during this time appears to be two-fold (100 to 250 cfs). Such a pattern may reveal that short-period trends may be part of longer-term cycles for groundwater; implications of this will be addressed later. Nutrient Analytes For Sequence A, nitrate increased strongly (19 springs with upward trends, only one down), while ammonia, phosphate, phosphorus, TKN, and total organic carbon showed little indication of trends. Since TKN, phosphorus, a nd total organic carbon decreased somewhat (though not significantly) it seems to indicate that nitrate-nitrogen alon e showed the strongest increase for SWFWMD. All other analytes showed little change or even evidence of a slight decline. Also unlike patterns s een in the rock and saline indica tors, nitrate increased during both sequences B and C. This is in c ontrast with the rock analytes which showed str ongest activity during Sequence C. Figure 38 and 39 illustrate nutrient trends and their variability for SWFWMD. Hunter and Magnolia Springs (Figure 38), illustrate clear in creases in nitrate over Sequence A. Nitrate increases occurred regardless of initial concentr ations at the beginning of the time series. For example, Hunter Spring (top) had a consistent increase from a low initial value (about 0.25 mg/L) to just under the SRA th reshold of 0.45 mg/L. Hunter re mained under the SRA value for the time period. Magnolia Spring showed a rate of increase similar to Hunter (SS = 0.0046 and 0.0042, respectively). However, Magnolia began th e time series with a higher starting value (about 0.35 mg/L). The trend for Magnolia crosse d over the SRA threshold (Figure 38, bottom, gray line marks SRA value). Similarly Weeki Wachee (Figure 39, top), began the time series

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BULLETIN NO. 69 67 with a value near 0.45 mg/L and increased to 0.8 mg/L by the end of the time sequence. All three springs had similar rates of change yet differe d in their initial concentrations of nitrate. Figure 36 Decreasing flow at Homosassa No. 1 Spring. Flow rates declined significantly from 1996 to 2003. (One cfs = 0.028 cms) Overall, TKN showed little activity (one tre nd up, four down for Sequence A). Figure 39 (bottom) shows a trend in TKN fo r Boyette Spring. It started with relatively low initial values and was followed with a rapid increase in 1998. Values went fr om near 0.5 mg/L to over 3.0 mg/L in short period of time. Field Analytes Only two Field analytes demonstrated decreasing trends over Sequence A, pH and temperature. The analyte pH decreased in 10 sp rings, while temperature decreased in eight. The trends for pH largely occurred in Sequence C. Wells The wells used for this study are a subdivision of FDEPs Background Network. The subdivision is referred to as th e Temporal Variability (TV) Ne twork. Although independent of springs, it was believed that eval uating trends in wells would shed insight as to the chemical behavior of Floridas groundwater The TV Network subdivides wells into whether they are confined or unconfined. Because of the small number of conf ined and unconfined wells per WMD, for districtwide and statew ide analyses, the wells were also combined into one pool (All). 1/2/19961/2/19981/2/20001/2/20021/2/2004 Date 40 60 80 100 120Flow (cfs) Homosassa No. 1 Spring Flow 12 40 60 80 100 120 LR p-value < 0.0001 n = 2879 WTp-value < 0.0001

BULLETIN NO. 69 71 Northwest Florida Water Management District Northwest Florida wells (Figur e 40) showed a lowering of water levels for Sequence A (six of eight wells were down, with no increasing trends). Temperature in creased in five wells, while the analyte sodium and sulfate increased in four wells. No wells demonstrated downward trends for temperature, sodium, and sulfate. The analyte pH decrea sed in four wells. Figure 40. Location of wells within the NWFWMD. Changes in sequences B and C reflected t hose in Sequence A. For Sequence B water level fell (six of eight wells had decreasing levels, while none increased). Several wells also showed increases in sodium (increased in four wells, decreased in none) and conductivity (increased in five we lls, decreased in none). Unlike springs, where the main influences on the chemistries occurred during Sequence C, the only notable analyte in well data demonstrating a change was pH. The analyte decreased in six of eight wells stud ied (and increased in none). Water Levels and pH Figures 41and 42 illustrate several of these tr ends. The association of water level and pH suggest a relationship between th e two analytes and will be disc ussed later. A drop in water levels occurred in both unconf ined and confined wells. Confined aquifer Well 312 (Figure 42) showed a 5 m (15 ft) decline over the period of record.

FLORIDA GEOLOGICAL SURVEY 74 Suwannee River Water Ma nagement District The locations of the SRWMD TV wells are displayed in Figure 43. Decreasing water level trends were observed in the SRWMD. Te mperature rose in Sequence C (seven increased and none decreased). Trends in Sequence A suggeste d the same pattern as in northwest Florida: declines in water level and pH. Figure 43. Location of wells within the SRWMD. Water Levels and pH Over the period of record, water level and pH trends looked similar to other districts. As two examples (Figure 44) of unconfined wells (Wells 1943 and 2465), a drop in water level appeared to be accompanied by a decrease in pH. Note that Well 2465 had rapidly declining water levels but a relatively slower change in pH. The water level decreased approximately 5 m (15 feet) by the end of the st udy. Confined groundwater showed similar patterns. Figure 45 shows water level and pH falling simultaneously for wells 2585 and 2675. In Well 2585, the water level drop is a minimum of 3 m (15 ft); some points in the early time series have substantially higher water level values [18 m (60 ft)] and sugge st the difference was even greater. By far the most extreme water level differen ce was recorded was Well 2675. From a high point of 27 m (90 ft) msl in 1994, water levels fell to approximately 9 m (30 ft) by 2003. This is nearly 18 m (60 ft) difference is due to its locati on near the Alapaha River. Local karst features create differences in water levels in response to rainfall. Like other wells in the district, Well 2675 experienced a decline in pH.

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BULLETIN NO. 69 75 Figure 44. Decreasing pH and water levels in SRWMD wells (#1943 and #2465). Both wells are unconfined. Tests (p < 0.05) included MK for trend, WT on se quences B and C, plus an SS calculation on rate of change. The begi nning sampling dates for wells are not the same. (One m = 0.3048 ft.)

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FLORIDA GEOLOGICAL SURVEY 76 Figure 45 Decreasing pH and water leve ls in SRWMD wells (#2585 and #2675). Both wells are confined. Tests (p < 0.05) included MK for trend, WT on Sequences B and C, plus SS calculations. Note beginning sampling dates for wells are not the same. (One m = 0.3048 ft.) St. Johns River Water Management District Figure 46 displays the location of TV Network wells in the SJRWMD. The trends for the wells shown in Figure 46 in the SJRWMD were slightly different from both the NWFWMD and

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BULLETIN NO. 69 77 Figure 46. Location of wells within the SJRWMD. the SRWMD. There were fewer wells with decreasing water level in the SJRWMD. However, decreases in pH were similar to the other WM Ds. The greatest proportion of decrease was in specific conductance. During Sequence A, zero increased while five decreased. During Sequence B one increased and four decreased, an d during Sequence C, one increased while five decreased. Along with specific c onductance, rock analytes such as calcium and alkalinity showed decreases for Sequence A. A number of wells showing an increase in temperature, both in Sequences A (six increased, one decreased) and Sequence C (four increased, two decreased). In Sequence C, increases in dissolved oxygen were notable. This occurred while pH was decreasing (none increased, four we lls decreased). Water levels had an unclear direction (four wells increased and only one decreased). Unlike other districts, pH d ecreased in many wells while water level tended to increase during Sequence C. Figure 47 shows both unconfin ed and confined groundwat er (Wells 1417 and 1763, respectively) in the SRWMD. Figure 48 shows th e relationship for a confin ed well (well 1762)

BULLETIN NO. 69 79 Figure 48. Temperature a nd specific conductance in SJRWMD well (#1762). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. in the SJRWMD. All the wells st art with different initial temp erature and specific conductance. Well 1417 temperature starts aroun d 22 C and ends over 23 C. Confined groundwater (Well 1763) starts near 22 C but ends slightly highe r. Though the slope is significant, a WT test between segments B and C show ed no significant differences (p-value 0.6739), indicating the amount of increase was less. At the same time, another confined well (Well 1762; Figure 48) had a clear temperature increase, starting near 24 C and ending near 26 C. Well 1417 began with greater than 400 S/cm specific conductan ce but ended with just above 300 (Figure 48, top). Slig htly more attenuated downward trends are present in the confined water (wells 1763 and 1762). Well 1763 showed trends within the range of 630 to about 600all within 30 S/cm. Well 1762 had a drop in specific conductance that was also over a relatively modest range of 760 700 S/cm (Figure 48). Southwest Florida Water Management District The SWFWMD wells (Figure 49) had the least amount of change among the WMDs. There were only a few cases worth noting. For Time Sequence A, six of 11 wells had temp

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FLORIDA GEOLOGICAL SURVEY 80 Figure 49. Location of wells within the SWFWMD. perature trends. Five of the six increased. Sequence B had four increases with no decreases in temperature. In Sequence C, water levels increa sed in four wells, while none decreased in none; specific conductance decreased in five wells but only increased in one.

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BULLETIN NO. 69 81 Like wells in the northern part of the st ate, water levels a nd pH often decreased significantly in a number of places in the SWFWMD Figure 50 illustrates de clining water levels and pH for two SWFWMD unconfined groundwater wells. Water level decreased at Well 996. At the same time, WT tests did not affirm di fferences between Sequence B and C water levels. The decreasing water level-trend was probably caused by the drought which occurred during Sequence C (low points are visi ble after the year 2000), but re covered after 2001. Thus, the overall reduction in water levels was relati vely small, when viewed from Sequence A (insignificant difference in the WT test). In contrast, Well 1087 had a significant reduction in water level and in pH. Well 707 (confined; Figure 51 ), along with wells 99 6 and 1087 (unconfined), demonstrated declining water levels that matche d trends toward the thr ee previously discussed WMDs. The pH levels in Sequences B and C in Well 707 indicated the lack of verifiable difference between the time sequences (WT test) although a MK test de tected a significant downward slope for pH. On the other hand, signif icant declines in wate r levels were observed. As with the unconfined groundwater, confined Well 707 showed a reduction in water level during the drought in 2000. For Sequence A, the si milarities in waterlevel changes in the SWFWMD and in the northern WMDs for springs and wells, suggested a statewide cause rather than only local influences. South Florida Water Management District Figure 52 displays the location of the wells in the SFWMD. A small number of trends were present for a variety of an alytes but nothing to suggested strong district-wide changes. The only possible exception was pH. For time Sequence C, of nine wells six registered trendsone increased and five decreased for pH. Examples of decreasing pH levels can be seen in two unconfined groundwater wells: 6490 and 3398 (Figure 53). The figure also demonstrates that water levels decreased in Well 6490. Relatively higher water levels at the start of the study may account for much of the change (Figure 53, top). The connection between pH and water level will be explored later. However, pH trends around the state were dominantly toward lower values. South Florida was no exception. Districtwide Spring Trends Maps depicting all of the trends for each analyte for each spring or well by water management district can be found in Appendix L. Evaluating individual trends is essential for this st udy. However, looki ng at trends from another scale can often be enlight ening. For example, were there districtwide or statewide areal trends present? The sign test ( = 0.05) was the major tool used for the analyses.

BULLETIN NO. 69 83 Figure 51. D ecreasing pH and water levels in SWFWMD well (#707). Water levels an d pH for Southwest confined groundwater (Well 707). Tests (p < 0.05) included MK for trend, WT on sequences B and C, plus an SS calculation on rate of change. Wakulla Spring is the only spring in the NW FWMD to have sufficient data for trend analyses. If only one station is present, a districtwide analysis for tre nds, based on the sign test, is not possible (Gilbert, 1987). For these reasons, and because Wakulla Spring is located only about 24 km (15 miles) to the SRWMD border, we included Wakulla Spri ng with the SRWMD. In addition, the SFWMD had no spring with suffi cient data for analyses. Thus, districtwide trends could only be conducted for the SRWMD (16 springs including Wakulla), the SJRWMD (14 springs), and the SW FWMD (27 springs). Recall (p. 59) that the after the delivery of Boyette Spring water quality data, the SWFWMD declassified Boyette as a spring. B ecause of the point-source dairy contamination, Boyette Spring data were removed from both dist rictwide and statewide analyses. Also, recall (p. 35) that the statistical test used to evaluate the presence of areal trends was the sign test (Appendix E). As used in this study, the sign test compares the pro portions of significantly increasing trends to significantly decreasing trends. If we were unable to confirm a trend, or if there were insufficient data, the corresponding sequen ces were not used for the sign tests. Note that for the sign test discussions that follow, the symbol + indicates an upward trend, - designates a downward trend, and a bla nk indicates no discernable trend. 2/12/199011/8/19928/5/19955/1/19981/25/200110/22/2003 Date 6.5 6.9 7.3 7.7 8.1pH 0 10 20 30WL (msl) pH WL (msl)Well 707 Time Sequence A: pH and WLpH MK p-value = 0.0045 nb = 82 nc = 34 WT p-value = 0.1627 SS = -0.0008 Water Level MK p-value = 0.0001 nb = 82 nc = 33 WT p-value = 0.0223 SS = -0.0592 12 6.5 6.9 7.3 7.7 8.1 12 0 10 20 30

FLORIDA GEOLOGICAL SURVEY 86 Districtwide Spring Trends in Suwannee River Water Management District The individual spring trends for Sequence A in the SRWMD (including Wakulla Spring) are displayed in Table 10. Significant trends were those with p-values less the 0.05. Flow had a significant decreasing trend while calcium, magnesium, sodium specific conductance, total kjeldahl nitrogen (TKN), and temperature each had upward districtwide tre nds (Table 11). The two far right columns of Table 10 summarize the total number of pluses and minuses for the respective analyte. Table 11 summarizes the anal ytes displaying district wide trends using the sign test, along with corresponding p-values. For Sequence B (Table 12), there were no obs ervable trends. Trends in Sequence C (Table 13) were similar to those in Sequence A. Table 14 summarizes Sequence C. Flow decreased, while calcium, ma gnesium, sodium, phosphorous and total kjeldahl nitrogen, had upward trends. Total organic ca rbon had a downward trend. Districtwide Spring Trends in St. Jo hns River Water Management District Spring trends for the SJRWMD are shown in Table 15. For Sequence A (Table 16) calcium, fluoride, pH, and strontium each had up ward trends while orthophosphate (or simply phosphate) had a downward trend. As with the SR WMD, no districtwide trends were observed for Sequence B (Table 17) within the SJRWMD. However, for Sequence C (Tables 18 and 19), flow had a downward trend while pH and fluoride had upward trends. Districtwide Spring Trends in Southwes t Florida Water Management District Individual spring trends for the SWFWMD are displayed in Table 20. For Sequence A (Table 21), bicarbonate (related to alkalinity), calcium, chloride magnesium, nitrate, potassium, sodium, specific conductance, strontium, sulfat e, and total dissolved solids, each had upward districtwide trends. The analyt es pH and temperature had downwa rd trends. Unfortunately, flow data were only available from three gaging stat ions within the SWFWMD. For this reason, there were insufficient data to make conclusions regarding districtwide flow trends. During Sequence B (Table 22), fluoride and nitrate each had an upward trend whereas phosphorus had a downward trend (Table 23). As with Sequence A, there existed insufficient data to determine significant flow trends during Sequence B. Sequence C was similar to Sequence A in term s of trends (Table 24). Bicarbonate, calcium, chloride, magnesium, nitrate, potassi um, specific conductance, sodium, strontium, sulfate, and total dissolved solids showed upwar d trends while pH had a downward trend (Table 25). Again there were insufficient data to dete rmine districtwide trends in flow. However, during Sequence C, three gaging stations did have sufficient data and all three of these sites demonstrated downward tr ends (Table 26).

BULLETIN NO. 69 99 Table 26. Spring Flow from Three Stations in the SWFWMD. Spring Location Trend Direction P-value Homosassa Springs at Homosassa Down <0.0001 Chassahowitzka River near Chassahowitzka Down <0.0001 Chassahowitzka River Near Homosassa Down <0.0001 For a summary of districtwide trends see Ta ble 27. The table displays the Sequence (A, B, and C) by WMD. It displays the analytes with upward and downward tr ends. In addition, it displays the corresponding p-values If a p-valu e is less than (significance level preset at 0.05), it is concluded that a districtwide trend exists. It should be noted that the lower the p-value, the lower the probability is that the null hypothesis (no trend) is true and, therefore, the stronger the argument for the existence of a trend. For example, a p-value of slightly less than 0.05 indicates that there was slightly less than one in 20 chance that a trend did not exist. If the p-value was 0.01, then there is only a one in 100 chance of th e error occurring. In addition to the authors presetting to be 0.05, they also, arbitrarily, set a pvalue of 0.02 as being strong evidence for a trend. Thus, a p-value less than 0.05, but greater than or equal to 0.02, was considered to be evidence for a moderately strong trend. Base d on this argument, the p-values in Table 27 represent strong evidence for trends. Table 27. Statewide Spring Trend Summary by WMD and Time Sequence. Light gray boxes indicate saline-related indicators, dark gray nutrient-related indicators. (p-values are from sign tests by the corresponding water management district) Sq SRWMD (including Wakulla Spring) SJRWMD SWFWMD A Up p-val Dwn p-val Up p-val Dwn p-val Up p-val Dwn p-val Ca 0.001 Flow 0.001 Ca 0.011 P04 <0.001 Ca 0.002 Tmp 0.004 Mg 0.002 F 0.001 Bcarb <0.001 pH 0.011 Na 0.002 pH 0.011 Mg <0.001 TKN 0.002 Sr 0.001 Sr <0.001 Tmp 0.008 K <0.001 Na <0.001 Cl <0.001 SO4 0.001 SC < 0.001 TDS <0.001 NO3 <0.001 B F 0.002 P 0.004 NO3 0.008 C Ca <0.001 Flow 0.002 pH 0.001 Flw 0.008 Ca 0.002 pH 0.016 Mg <0.001 TOC 0.003 F 0.008 Bicarb <0.001 Na <0.001 Mg <0.001 P 0.002 Sr <0.001 TKN 0.001 K <0.001 Na <0.001 Cl <0.001 SO4 <0.001 SC <0.001 TDS 0.004 NO3 0.006 Bcarb = Bicarb; Dwn = Down; Flw = Flow; Tmp = Temp

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FLORIDA GEOLOGICAL SURVEY 100 Statewide Spring Trends It should be pointed out that bicarbonate was sampled only by the SWFWMD. However, the other WMDs sampled alkalinity. The two species are considered to have sufficient similarities to be considered one analyte (b icarbonate/alkalinity spec ies) for the sign test exercises. Tables 28-30 show analytes with statewide trends for each time sequence. For Sequence A (Table 28), analytes showing upward statewide trends were alkalinity, calcium, chloride, fluoride, magnesium, nitrat e, potassium, sodium, specific conductance, sulfate, strontium, and total dissolved solids. Flow was the only analyte with a downward trend. For Sequence B (Table 29), the sign tests reveal ed that nitrate and F had upward trends, while phosphorus showed a decreasing trend. For Sequence C (Table 30), the sign tests indi cated that alkalinity, calcium, chloride, fluoride, magnesium, nitrate, potassium, sodium, specific conductance, sulfate, strontium, and total dissolved solids, and total kjeldahl nitr ogen each had upward trends, while flow and total organic carbon demonstrated downward trends. Except for flow, the analytes with statewide trends were the same in Sequence C as they were in Sequence A. No statewide trend determination for flow for Sequence B could be made because of insufficient data. Table 28. Statewide Trends Based on Sign Tests for 57 Springs, Sequence A (1991-2003). Analyte + Trend Direction P-Value Alk 29 1 Up <0.001 Ca 31 2 Up <0.001 Cl 27 4 Up <0.001 F 16 0 Up <0.001 Flow 3 14 Down 0.006 K 20 3 Up 0.001 Mg 32 2 Up <0.001 Na 30 4 Up <0.001 NO3 25 11 Up 0.020 SC* 24 9 UP 0.014 SO4 27 8 Up 0.001 Sr 27 1 Up <0.001 TDS 18 2 Up <0.001 *Specific conductivity SWFWMD and SJRWMD measured specific conductivity (field); SRWMD measured specific conductivity (lab). Table 29. Statewide Trends Based on Sign Tests for 57 Springs, Sequence B (1991-1997). Analyte + Trend Direction P-Value NO3 7 1 Up 0.034 P 0 16 Down <0.001 F 12 0 Up < 0.001

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BULLETIN NO. 69 101 Table 30. Statewide Trends Based on Sign Tests for 57 Springs, Sequence C (1998-2003). Analyte + Trend Direction P-Value Alk 27 2 Up <0.001 Ca 23 1 Up <0.001 Cl 24 6 Up 0.001 F 16 0 Up <0.001 Flow 0 20 Down <0.001 K 23 1 Up <0.001 Mg 28 1 Up <0.001 Na 28 1 Up <0.001 SC* 20 5 Up 0.003 SO4 21 6 Up 0.004 Sr 22 1 Up <0.001 TDS 10 0 Up 0.002 TKN 10 2 Up 0.020 TOC 2 15 Down 0.002 Specific conductance SWFWMD and SJRWMD measured specific conductance (field); SRWMD measured specific conductivity (lab). Constrained Version of Statewide Trends A second, more constrained, criterion was also used in the sign test evaluation. For these analyses, in order for an analyte to be considered to have a statewide tren d, not only did it need to show a significant statewide trend based on a sign test, there also needed to be significance in at least two of the three WMDs Since several springs are located within a common springshed, the areal clustering of these latter springs can po tentially be influenced by springs having highly correlated water chemistries. For Sequence A (Table 31), using the more constrained approach, calcium, magnesium, and sodium showed increas ing statewide trends while no analyte had decreasing trends. There were insufficient flow data in the SWFWMD and, using the two-WMD criterion, no statewide trend determination could be made for flow. There were no statewide trends for analytes using the constrained tw o WMD criteria for Sequence B. However, for Sequence C, Table 32 indicates that flow decrea sed statewide, while ca lcium, magnesium, and sodium increased. Because of lack of availabl e space in many of the following tables, abridged abbreviations are assigned to each WMD for both spring and well tables. They are as follows: NWFWMD (NW), SRWMD (SR), SJRWMD (SJ), SWFWMD (SW), and SFWMD (SF). Table 31. Statewide Trends in at Least Two WMDs, Sequence A (1991-2003). (Statewide trend and districtwide trend in at least two WMDs.) Analyte + Sig in WMD Trend Direction P-Value Ca 31 2 SR, SJ, SW Up <0.001 Mg 32 2 SR, SW Up <0.001 Na 30 4 SR, SW Up <0.001 SR = SRWMD, SJ = SJRWMD, SW = SWFWMD

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FLORIDA GEOLOGICAL SURVEY 102 Table 32. Statewide Trends in at Least Two WMDs, Sequence C (1998-2003). (Statewide trend and districtwide trend in at least two WMDs.) Analyte + Sig in WMD Trend Direction P-Value Flow 0 19 SR, SJ Down <0.001 Ca 23 1 SR, SW Up <0.001 Mg 28 1 SR, SW Up <0.001 Na 28 1 SR, SW Up <0.001 SR = SRWMD, SJ = SJRWMD, SW = SWFWMD Independence of Springs and Wells According to Conover (1999), a sign test makes three assumptions. First, the measurement scale is at least ordinal within each pair. For this study, each pair may be determined to be a plus, a minus or a tie. Second, the pairs need to be internally consistent. That is, the probability of any one pair being plus (or minus) is the same for all pairs. Third, the pairs of data are considered to be mutually independent bivariate random variables. The three assumptions are discussed in detail in Appendix E. For the analyses in this report, the first two assumptions are readily achieved. However, the third assumption was not always met. Although sampling stations are often considered to be randomly located, and each analyte to be a random variable, it is not always correct to assume that the pairs of da ta are mutually independent. Some of the springs are located within a common sp ringshed. Because of their proximity to one another, the analyte concentration in one spring may (but not necessarily) be highly correlated with other springs within the springshed. Likewise some of the wells are in clusters; that is, the wells are located next to each other, but tap di fferent aquifers. Like springs, because of their proximity to one another, the concentration in one well may be highly correlated (but not necessarily) with the other wells in the cluster. Note the farther a station is located from a second one, the less likely the two are hi ghly correlated with each other. One way to deal with the proximity problem would be to randomly select one spring from each springshed, or one well from each cluster. This effort will reduce the dependency issue. However, it will also reduce the number of springs and wells available for analyses. Because it was very difficult to find springs and wells with sufficient data for trend analyses, it was not desirable to elim inate sampling stations. Because some of the wells are clusters, dependency due to the close proximity of wells to one another, can be, and probably is, a problem in the evaluation of well water-quality trends. Three clusters of two wells are found in the NWFWMD. Two clusters of three wells and one cluster of two wells are found in the SJRWMD. One cluster of th ree wells and two clusters of two wells are found in the SWFWMD Finally, two clusters of tw o wells are in the SFWMD. For statewide trends, the best way to combat the problem is to: (1) emphasize analytes with strong trend signals (e.g. p-values < 0.02) a nd (2) emphasize which analytes demonstrate significant trends in, for example, at least three of the five WMDs Quantifying the effect of dependency can be difficult. However, the strength of the statewide (and districtwide) trend signals (p-values) can assist in evaluating the dependency issue

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BULLETIN NO. 69 103 for this project. Table 33 displays the statewide plus/minus chart for Sequence A for Alk/Bicarbonate, calcium, magne sium, strontium and fluoride for the 57 springs. The table reveals that for Alk/Bicarb, there were 29 + values and zero - values. For Sr, there were 27 + values and only one -. For both analytes, the p-values of the sign test were <0.001. Notice in the cells in Table 33 that contains the values 29 for Alk/Bicarb and 27 fo r strontium, there is a 12* in parentheses and an 7** in parentheses resp ectively. The asterisk next to the 12 indicates that if there is no - value, one could have as few as 12 + valu es and still have a p-value less than 0.001. The double asterisk next to the 7 indicat es that if there is no - value, one could have as few as seven + values and still have a p-value less than 0.05 (the level of significance). Since there were 29 and 27 + values for Alk/Bi carb and strontium respectively, it is highly unlikely that dependency is a major factor regard ing whether or not there are statewide trends. Table 33. Selected Statewide Analyte Results, Sequence A (1991-2003). Analyte + <0.01 <0.05 Direction P-Value Alk/Bicarb 29 (12*) (7**) 0 Up <0.001 Ca 31 (18*) (9**) 2 Up <0.001 Mg 32 (18*) (9**) 2 Up <0.001 Sr 27 (16*) (8**) 1 Up <0.001 F 16 (12*) (7**) 0 Up 0.007 Min. # of + and still have a probability value (P-Val) <0.001 with a given number of values ** Min. # of + and still have a probability value (P-Val) <0.050 with a given number of values Also in Table 33, note that for the rows co rresponding to calcium and magnesium, there were 31 and 32 + values respectively and, for both analytes there were only two - values. The single and double asterisks indicate that if th ere were only two - values, one could have as few as 16 + values and still have a p-value of less than 0.001. One could also have as few as 9 + values and still have a p-va lue of less than the significance level of 0.05. Since, for each analyte, there were 31 and 32 + values respectively, it is highly unlikely that dependency is a significant issue when stating there are statewide trends for these analytes. Table 27 indicates that the p-values are overw helmingly, on a districtwi de basis, less than 0.02. In addition, most analytes displaying statew ide trends in Tables 28 30 have very low pvalues (generally less than 0.02). Because of the high proportion of extremely strong trend signals (low p-values), the authors conclude that although dependency is an issue to be aware of, it is not a major issue with regard to districtwide and statewide trends fo r springs for this study. Districtwide Well-Water Trends The number of wells with sufficient data for trend analyses varied per WMD between eight and 11. In addition, wells w ithin a district were labeled as withdrawing water from either: (1) unconfined groundwater or (2) confined groundwater. However a third categorized was used for statistical analyses. It was a combination of both categories (all wells combined). As with any statistical test, the smaller th e sample size, the more difficult it is to find enough evidence to reject a null hypothesis. Th e combined (All) category had the eff ect of increasing the sample size of wells per WMD.

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FLORIDA GEOLOGICAL SURVEY 104 Several indications of changing groundwater quality were observed. The basis of the evidence is arbitrary and two crit eria were used. They were: A. Number of wells showing a trend in majo r the direction exceeds minor direction by greater than a two to one margin, and B. Number of wells in major direction must exceed number minor direction by at least four. For example, Table 34 reveals that the number of wells with decreasing trends in water levels [WL(msl)] is six and that the number with increasing trends is zero. Since the number of decreasing trends (dominant direction) exceed s the number with increasing trends (minor) direction by at least four, we made the interpretation that the NWFWMD had a decreasing districtwide trend in water le vels for Sequence A. The criteria was used for unconfined, confined, and the combined categories. In a nother example, also for Sequence A in the NWFWMD in the combined cate gory, dissolved oxygen had downward trends in four wells and one well demonstrated an upward trend. Even though there is a dominance of downward trends, the number of wells with downward trends did not exceed the number with upward trends by at least four. Thus, the authors did not consider the existence of a potential downward trend for dissolved oxygen fo r the NWFWMD. Evidence of Districtwide Well Water-quali ty Trends Northwest Florida Water Management District Data from eight wells (six unconfined and two confined) in the NWFWMD were used. For unconfined groundwater for Sequence A, sodium sulfate, and temperature showed potential evidence for upward trends, while pH and wate r levels (WL[msl]) demonstrated potential evidence for downward trends (Table 34). Usi ng the criteria mentioned above, with only two wells tapping confined groundwater, potential evidence for districtwide trends did not exist. For the combined category (All), potential evidence for upward trends existed for temperature, while water levels demonstrated a potential downwar d trend. Table 35 displays the plus/minus (upward/downward) results for Sequence A for the NWFWMD. It also lists several potential reasons for the changes in water quality and quantity. Table 36 displays the trend results for Seque nce B. For unconfined groundwater, sodium and field specific conductance (SC-fld) had a potential increase. For the combined category, SCfld increased while water levels decreased (Tab le 37). For Sequence C (Table 38), the only analyte demonstrating evidence for trends was pH. For unconfined groundw ater, as well as the combined category, it demonstrated a poten tial downward trend (Table 39).

BULLETIN NO. 69 121 solids. Fluoride had an increasing tre nd while phosphorous had a decreasing trend during Sequence B. Trends during Sequence C were the same as those in Sequence A. Table 63. Statewide Spring-water Quality Summary for Rock and Saline Indicators. (Only indicators displaying strong significant trends (P-Value < 0.020) Sequence A (1991 2003) Analyte Trend Direction P-Value Flow Down 0.006 Alk Up <0.001 Ca Up <0.001 Cl Up <0.001 F Up <0.001 K Up 0.001 Mg Up <0.001 Na Up <0.001 SC Up 0.004 Sr Up <0.001 SO4 Up <0.001 TDS Up <0.001 Sequence B (1991-1997) F Up <0.001 P Down <0.001 Sequence C (1998-2003) Flow Down <0.001 Alk Up <0.001 Ca Up <0.001 Cl Up 0.001 F Up <0.001 K Up <0.001 Mg Up <0.001 Na Up <0.001 SC Up 0.004 Sr Up <0.001 SO4 Up 0.003 TDS Up 0.033 Constrained Version of Statewide Trends for Groundwater More constrained criteria were also used in the sign test evaluation for combined groundwater. For these analyses, in order for an analyte to be considered to have a statewide trend, not only did it need to s how a statewide trend ba sed on a sign test, it al so needed to have evidence of a districtwide trend in at least three of the five WMDs. Regarding combined groundwater resources, Table 64 in dicates that for Sequence A, calcium, pH, and water levels had downward trends, while temperature had a st atewide increasing tre nd. All were strong

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FLORIDA GEOLOGICAL SURVEY 122 trends. The analyte pH had a strong downwar d trend during Sequence B while temperature had a strong upward trend and pH had a strong downward trend during Sequence C. Table 64. Statewide Trends for at Least Three WMDs: Sequences A, B, and C for Combined Groundwater Resources. Statewide Sequence A ( 1991-2003) Trends in at Least three WMDs Analyte + Eviden ce in WMD Trend Direction P-Value* Ca 3 11 SR, SJ, SW Down 0.018 pH 3 20 NW, SR, SJ, SW, SF Down <0.001 Temp 20 8 NW, SJ, SW Up 0.018 WL(msl) 4 18 NW, SR, SW, Down 0.002 Statewide Sequence B (1991-1997) Trends in at Least 3 WMDs Analyte + Evidence in WMD Trend Direction P-Value* pH 2 11 SR, SJ, SW Down 0.003 Statewide Sequence C (1998-2003) Trends in at Least 3 WMDs Analyte + Evidence in WMD Trend Direction P-Value* pH 5 18 NW, SJ, SF Down 0.006 Temp 15 4 NW, SR, SJ Up 0.010 In addition to a p-value <0.05, there must be signif icant trends in at least three of the five WMDs. DISCUSSION Recall that the definition of a constr ained statewide trend was that at the = 0.05 level of significance for springs, analytes al so had to have statistically significant trends using the sign test in two of the three WMD regions [(1) SR WMD plus Wakulla Spring, (2) SJRWMD, and (3) SWFWMD]. For wells, analytes had to have statistically significant statewide trends using the sign test and evidence of district wide trends needed to exist in three of the five WMDs. Considering the constrained versions of statewid e trends, Table 65 summarizes the results. For spring-water quality, calcium, magnesium, and s odium had increasing trends during Sequences A and C. In addition, strontium had an upwar d trend during Sequence A, while flow had a decreasing trend for Sequence C. For combin ed groundwater, during Sequence A, temperature increased while calcium, pH, turb idity, and water levels decreased significantly. For Sequence B, pH decreased while for Sequence C, pH decreased and temperature increased. Spring-water quality is considered an integr ator of what affects groundwater during its flow path from the recharge area to the spring di scharge point. Regarding springs, there were no strong rock and saline trends during Sequence B. Because of the highly correlative relationship among the rock and saline indicators during Sequen ce A and C, it indicates that the time period of Sequence C (1998-2003) was the one in which mo st trends developed and is also when the drought occurred. The evidence de rived from well-water quality is not nearly as strong. However, there is supporting evidence. Regard ing well-water quality, no strong trends occurred during Sequence B. The indicator pH had strong decr easing trends in Sequence A and C and a significantly decreasing tre nd during Sequence B.

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BULLETIN NO. 69 123Table 65. Constrained Statewide Spring and Groundwater-quality Summary. Sequence Springs* All GW** (Unconfined and Confined) A (1991 2003) Ca Ca Mg pH Na Temp Sr WL(msl) B (1991 1997) pH C (1998 2003) Flow pH Ca Temp Mg Na *Significant in at least tw o water management districts. **Significant in at least three water management districts. Major Cause of Statewide Trends: Drought and Consequential Saltwater Encroachment From a districtwide or a statewide perspective, if regional trends di d not exist, one would expect, for a given analyte, a similar number w ould increase as would decrease. However, the results of sign tests in this study, especially on th e statewide scale, indica te that for springs the rock-matrix and the saline indicato rs were the two groups that had the vast majority of area-wide trends for Sequences A and C. In wells, the field indicators, such as temperature, water levels and pH, were the ones that displaye d large, area-wide trends. Di strictwide and statewide trends occurred mostly in Sequences A and C, but not very often in Sequen ce B (1991-1997). What are the causes of the rock, saline, and field indicator trends? Are the causes related? Is there one overall reason for the trends, or ar e there a variety of reasons? The most severe portion of the drought occurred during the 1999-2000 time frame (Verdi et al., 2006). Could the reasons for the area-wide trends be related to the drought? If saline indicators trended upward during the study period, is it an indica tion that Florida experienced saltwater encroachment on a regional and/or statewid e scale? We decided that for this paper, we would differentiate between the terms saltwater encroachment and saltwater intrusion. As modified from Neuendorf et al. ( 2005), saltwater encroachment is defined as the displacement of fresh groundwater by the advance of saltwater due to its greater density. Freeze and Cherry (1979) use the term intrusion as the migration of saltwater into freshwater aquifers under the influence of groundwater development. For our purposes, intrusion indicates a man-induced process while encroachment makes no such distinction between natural and man-made causes Because the drought lasted for much of the 13-year time frame of the study, we addressed the drought-related questions by reviewing annual weather data for Sequences B and C. We believed that these data could shed light on the behavior of field indicators such as temperature, spring flow, and water level. Temperature was addressed first. Table 66 displays mean annual statewide temperatures and rainfall for Sequences B and C, based on data from the Southeastern Regional Climate Center (2006). Regarding air temperature (Table 66), there were 84 SERCC

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FLORIDA GEOLOGICAL SURVEY 124 weather stations in Florida with sufficient da ta to calculate annual means for the 1991-2003 time period. For these stations, the mean temperature for Sequence B was 22.12 C (71.81 F) and the mean for Sequence C was 22.23 C (72.02 F), a slig ht increase. Figure 54 depicts the year to year changes in mean temperature. Table 66. Summarized Annual Weather Data in Florida (1991-2003). Category Sequence B (1991 1997) Sequence C (1998 2003) Difference (Seq. C Seq. B) Mean Air Temperature (84 Weather Stations) 22.12 C (71.81 F) 22.23 C (72.02 F) + 0.12 C (+ 0.21 F) Mean Rainfall (88 Weather Stations) 139.64cm/yr (54.98 in/yr) 127.76 cm/yr (50.30 in/yr) +11.89 cm/yr (4.68 in/yr) Regarding rainfall (Table 66), there were 88 stations with sufficient data to calculate annual means. For Sequence B, the mean was 139.64 cm/yr (54.98 in/yr). For Sequence C, the mean was 127.76 cm/yr (50.30 in/yr). Figur e 54 indicates that beginning in 1999 and continuing through 2000, Florida e xperienced a very dry period. It began one year after the beginning of Sequence C. During Sequence C, th ere was a deficit of between 10 and 13 cm/yr (four and five in/yr) of rainfall a nnually relative to Sequence B. With reduced rainfall, there was less recharge to groundwater and, conse quently, spring flow declined. In searching for an explanation for the st atewide trends, the drought and saltwater encroachment can explain virtually all of the rock-matrix and sali ne-indicator trends. Recall that Floridas fresh groundwater forms a lens of freshwater that, because of its lower density, overlies saline water. During periods of abundant rainfall, aquifer rech arge exceeds discharge and the freshwater lens increas es in size. However, during the states periodic droughts, the rate of aquifer recharge is less than discharge and the lens shrinks in size. With less recharge, the potentiometric surfaces of aquifers are lowere d and spring flow declines. As they decline, we believe that younger and freshe r groundwater discharging from sp rings is eventually replaced by deeper and older water. The deeper water c ontains more minerals (transition zone water) because it has been in the aquifer system for a longer period of time. This idea is supported by Upchurch (1992) and Ka tz (2004). Figure 55 illustrates the relative position among sea water, transition water (including both outer and inner) and freshwater within the Floridan aquifer system. Note the relationship between outer and inner transition water. The outer contains a greater proportion of saline indicators, while the inne r water contains a greater percentage of rock-matrix analytes. Figure 56 depicts a schematic of possible en croachment before and during a drought. During the drought, aquifer water levels decline, inferring that the fresh water lens decreases in size. Coastal springs, or springs that are tidally influenced, experience lateral encroachment of sea water. Inland springs can also be affected. Encroachment can occur because of the potential replacement of older and denser saline water at the base due to the lowering of the head in the Upper Floridan aquifer system. If the potentiometric surface of the UFAS become less than the aquifers lying below the UFAS, saline water can invade from below.

FLORIDA GEOLOGICAL SURVEY 126 during Sequence C, on a statewide basis, we infe r saline encroachment did occur and that the extent varied across the state dependi ng on the severity of the drought. During a drought, there is less surface water runoff. Thus, there is not as much young less-mineralized surface water recharging Floridas aquifers through swallets and sinks. Again, this is favorable for increasing trends in ro ck and saline indicators in spring discharge. Figure 55. Relative position of rock-matrix and saline analytes in the Upper Floridan aquifer system. Drought Verdi et al. (2006) mentioned that a drought is a time of less-than-normal or expected rainfall. It can be thought of as a period of time when there is insufficient water to support the agricultural, urban or environmental needs of a society. They also stated that a hydrological drought is an extended period during which stream flow, la ke, reservoir storage, and groundwater levels are below normal. Referring to a drought, Jackso n (1997) said, In general, an extended period of dry weather or period of deficient rainfall that may extend over an indefinite number of days. There is not a quantitative standard to determine th e degree of deficiency needed to constitute a drought. Qualitatively, a drought may be defined by its effect as a dry period of sufficient length and severity to cause at least partial crop failu re or having impacted the ability to met normal water demand.

FLORIDA GEOLOGICAL SURVEY 128 According to Henry (1998), the 30-year aver age (1961-1990) rainfall in Florida was just over 53 inches (135 cm) per year For the 1999 and 2000 time frame, Florida had a deficit of over 30 inches (76 cm), relative to its 30-year mean. Also, since the average rainfall during Sequence C was only 50.30 inches/yr (127.8 cm/yr), Florida was in a drought. In fact, in 2001 the FDEP and the Florida Department of Commun ity Affairs (2002) stated that, at that time, Florida was in the midst of an historical seve re drought. The severity of the statewide drought varied depending on the local precipitation (Appendix M). Thus, the severity of the drought and the corresponding saltwater encroachment also varied across the state. Rock-Matrix and Saline Indicator Evidence in Spring-water Quality In Florida, recharge generally occurs firs t in the uppermost portion of aquifers and recharge water is younger than deeper water. T hus, during times of less recharge as spring flow is reduced, the proportion of older (transition) wa ter increases. The older water is enriched in rock-matrix analytes. The fact that rock and sa line indicators demonstrated strong increasing trends across the state (Tables 27-30), while flow had a strong decreasing trend is a compelling argument that Floridas freshwater lens decreased in size and saltwater encroachment did occur during Sequence C. Unfortunately, determining the locations where the actual encroachment took place cannot be determined w ith these sets of data. In the future, better monitoring should allow the state to make these determinations. Rock-Matrix and Saline Indicator Evidence in Well-water Quality Recall that the wells used for th is report are TV wells and that they tend to be relatively shallow. Although the maximum depth of any of the wells used in this study is 1000 feet, 50 percent of the wells are between 57 and 161 feet (17 and 49 m) (Appendix C) and, as previously stated, the median depth of the wells is 80 feet (24 m). The wells generally tap the upper portion of the corresponding aquifer. Figure 57 is a diagram of an unconfined well. Note the relative position of the well intake zone (well screen) to the water table. Under our hypothesis, gr oundwater just below the water table has the lowest pH. During wet periods (Figure 57, top) the distance from the intake zone to the water table (static water level) is at its maximu m. During the drought (Figure 57, bottom), the water table was slowly lowered. As it dropped, a greater and greater proportion of groundwater with lower pH found its way into the well intake zone. As the drought continued, water levels, along with pH, decreased. There is no evidence that pH decreased throughout the groundwater column only that th e water table, with the most acidic water, moved downward closer and closer to the well intake zone during the drought. Other explanations can explain the correlation between water level and pH. For example, D. Harrington (FDEP, personal communications) suggested that the lowering of the water table and subsequent oxidation in the uppermost porti on of the saturation zone during a drought, could lead to a release of reduced sulfur compounds and a subsequent lowering of pH. P. Hansard (Colorado School of Mines, personal communicati ons) supported Harringtons interpre tation.

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BULLETIN NO. 69 129 Figure 57. Water level and pH relat ionships for a well with a falling water table. Top (Time 1) the upper portion of the water table gene rally consists of recently recharged, low pH metoric water. Botom (Time 2) heavy pumping and drought cond itions lower the water table, introducing progressively lower pH water to the well screen. As the water table is lowered, low pH water near the top of the water table moves closer and closer to the well screen.

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FLORIDA GEOLOGICAL SURVEY 130 As water levels decreased, dissolved oxygen could increase in the vicinity of the well. The increases in aerobic microbial respiration c ould increase carbon dioxide content, and consequently lower pH. He noted there did not need be a net change in pH in the entire groundwater column; simply that the zone of maximum respiration (e.g. the water table) got closer to the well screen during the drought. Although the specific s are not totally understood, the hypothesis that the lowering of pH is related to the lowering of water le vels is testable. As Florida fully recovers from the drought, water levels and pH values should increase. Table 62 indicates that for combined groundw ater during Sequence A, decreasing trends occurred, not only for both water level and pH, but also for temperature, turbidity and calcium. Groundwater temperature increased statewide, while turbidity and calcium decreased. The most plausible explanation is that groundwater temper ature increased as air temperature increased. Recall that most of the 46 wells were relatively shallow. An inspection of air temperature (Southeast Regional Climate Center, 2006) reveal ed that air temperature increased during Sequence A. An addition, spring wa ter, which is an integrator of the entire springshed, both deep and shallow, had no temperature trends. Regarding turbidity, no districtwide trends were observed and the only statewide trend occurred during Sequence A for combined (unc onfined and confined) groundwater. Appendix B1 indicates that turbidity is a measure of light to pass through a water sample. It is caused by particulate material suspended in the water and colloidal material that hinders light penetration. The source of turbidity is ofte n from surface water that contains high concentrations of humic substances and/or particulate matter, chemical reactions that result in the precipitation of colloidal material and certain forms of pl ankton growth. During the drought, less water originating from land surface can find its way in to wells. Thus, the drought is a plausible explanation for the decreasi ng trends in turbidity. The reason for the decr easing trend in calcium in wells is not fully understood. Calcite precipitation increases with increasing temperature. Thus, the increasing in temperature may be a cause for decreasing calcium concentrations. Paradoxically, increases in carbon dioxide near the well intake zone as water levels decreased (Figure 57) should cause calcite dissolution, and raise calcium concentrations. Mo re research is needed in orde r to fully understand the positive correlation between water levels and calcium concentrations. Regional to Sub-Regional Eviden ce of Saltwater Encroachment In springs, rock-matrix and sa line indicators demonstrated st rong increasing trends across the state (Tables 27-32) while flow had a strong decreasing trend. Together they are compelling arguments that Floridas freshwater lens decr eased in size and saltwater encroachment did occur during Sequence C. Annual mean temperat ure and precipitation data for each station, and for each WMD, are found in Appendix M. The da ta were used to cal culate the weighted statewide means (weighted by the number of stations in each WMD) for rainfall used in the time series plots in Figure 58.

FLORIDA GEOLOGICAL SURVEY 132 Consider the donut. It had different weather conditions, rela tive to the donut hole. For the donut, during Sequence B, the temp erature averaged 22.01 C (71.61 F) and for Sequence C, the mean temperature was 22.17 C (71.90 F), an increase of 0.16 C (0.29 F). Regarding precipitation, during Sequence B, the donut averaged 142.60 cm/yr (56. 14 in/yr) of rain, and during Sequence C, it averaged only 126.42 cm/yr (49.77 in/yr), a deficit of 16.18 cm/yr (6.37 in/yr). Interestingly, during the worst of th e drought (1999-2000) the SWFWMD donut hole region suffered severely (Verdi et al., 2006). As it turns out th e SWFWMD region was also drier during Sequence B, relative to the rest of the state (Figure 58). Nevertheless, during the last two years of Sequence C, it recovere d and actually had a more normal rainfall than the remainder of Florida (Figure 58). Now consider each WMD. If one subtracts the mean rainfall during Sequence C from the mean of Sequence B at each rain station, then Tabl e 68 indicates that the nu mber of rain stations in the NWFWMD with an increase in rainfall was one, while the number with decreasing rainfall was eight. Using a sign test, the correspondin g p-value was 0.020, and thus, there existed a downward trend in annual mean rainfall for the NWFWMD. The table also indicates that downward trends existed in the SRWMD, the SJRWMD, and the SFWMD. However, no trend was present in the SWFWMD donut hole. To re iterate, in terms of rainfall, for Sequence C, the SWFWMD suffered severely during the worst part of th e drought (1999-2000) but only suffered mildly, relative to the rest of Florid a, if one considers the entire 1998-2003 Sequence C time frame. Table 68. Summarized rainfall, Sequence C minus Sequence B. WMD + P-Val Trend NWFWMD 1 8 0.020 Down SRWMD 0 11 <0.001 Down SJRWMD 2 19 <0.001 Down SWFWMD 12 10 0.416 No Trend SFWMD 6 19 0.007 Down Number of stations in which rainfall in Sequence C > than same station in Sequence B = + Number of stations in which rainfall in Sequence C than same station in Sequence B = (Source: Southeast Regional Climate Center, 2006) In spite of the relatively mild effect of decreased rainfall during the entire duration of Sequence C, there were many indications that th e spring-water quality within the donut hole suffered severely. Table 27 displays the analytes with trends for each of the three time sequences for springs. Note the discussion that follows may be indi cative that the severe effect denoted earlier may not have had time to revers e. On the other hand, it may indicate that saline encroachment (or even intrusion) was a problem during Sequence C. Recall that during Sequences A and C, we cons ider increasing trends in saline and rockmatrix indicators, along with decreasing trends in spring flow and water levels, to be an indication of a decreasing volume of fresh water in Floridas aq uifers and an indication of

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BULLETIN NO. 69 133 saltwater encroachment. As spring flow decrea sed, spring discharge water was replaced with older, more mineralized water. The statew ide changes in groundwat er quality, along with statewide decreases in aquifer potentiom etry, support this perspective. For the following analysis consider Wakulla Spring to be part of the SRWMD. If one only considers saline (including flow) and rock-matrix indicators for Sequence A in the SRWMD (plus Wakulla), flow decreased while ca lcium, magnesium, and sodium increased. For the SJRWMD, calcium, fluoride, and strontium increased. However, for the SWFWMD, ten rock and saline analytes had increasing trends They were calcium, bicarbonate, magnesium, strontium, potassium, sodium, chloride, sulfate, sp ecific conductance, and total dissolved solids. During Sequence C, strong trends were obser ved in seven saline indicators in the SWFWMD: strontium, potassium, sodium, chlori de, sulfate, specific conductance, and total dissolved solids had upward trends In addition, three rock indicators: calc ium, bicarbonate, and magnesium had upward trends. Suff icient spring flow was only ava ilable at three stations in the SWFWMD (Homosassa Springs, Chassaho witzka River near Chassahowitzka, and Chassahowitzka River near Homosassa Springs) Flow was observed to decrease (see Homosassa and Chassahowitzka Springs in Tabl e 26 and Appendix K). Data from only three springs are insufficient to estimate a regional trend. However, it is plausible, that if additional spring flow data were available, they would demonstrate that significant downward trends in spring flow in the SWFWMD did occur. The increasing trends in saline and rock indi cators indicate that salt-water encroachment occurred during Sequence C. Although data suggest s that encroachment was most severe in the SWFWMD, because the concentrati ons of saline analytes increa sed almost everywhere in the state during the drought, it is an in dication that encroachment occurr ed on a statewide scale. The 1998-2002 drought was one of the worst histor ical droughts to aff ect Florida (Verdi et al, 2006). In order to make up for the drought groundwater pumping increa sed (Verdi et al., 2006). Because an increase in groundwater pumpi ng occurred during one of worst droughts, it is likely that human-induced saline intrusion took place. On a statewide scale, the extent and severity of the intrusion is difficult to quantify. However, within the northern portion of the SWFWMD, a water budget and a regional groundwater flow model indicated that the effect of groundwater withdrawals was less than 2.0% of the e ffect due to the loss of recharge because of decreased rainfall (Ron Basso, personal communications). Nevertheless, intrusion should be a concern. If another drought of this magnitude occurs, depending on the amount of increased pumping, it could potentially have adverse affect s on the long-term sustai nability of Floridas groundwater resources. Groundwater Withdrawals The Florida Department of Environmental Pr otection (2008) stated that water use in Florida will increase as Flor idas population grows. The population in 1990 was officially 12,937,926. In 2000 it was 15,982,378 and by 2003 it was 16,713,149 (U.S. Census Bureau, 2006). Over those 14 years, it grew by 3,775,223, an increase of over 730 people per day.

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FLORIDA GEOLOGICAL SURVEY 134 According to Marella and Berndt (2005), Fl oridas groundwater withdrawals for all water use categories (agriculture, publ ic supply, commercial/industrial, recreation, domestic, and power generation) in 2000 exceeded 3.1 billion gallons per day. Of those categories, agriculture and public supply accounted for over 82 percent. If divided evenly amongst the population, in 2000, over 190 gallons per day (gpd) of groundwater were used by each person of the state. Since Floridas population is growing by 730 peopl e per day and each new person is using over 190 gpd, then the demand for grou ndwater increases by more th an 135,000 gpd or by more 50 million gallons per year. Because of the lack of precipitation, in an effort to make up for the lack of rain, the pumping of groundwat er typically increased during droughts. Thus during Sequence C the drought, the increased population and the in crease in consumption of groundwater each had a negative impact on both the quantity and quality of Floridas gr oundwater resources. Groundwater Summary Groundwater quantity and quality data indicates that during Sequence C, Florida suffered from natural saltwater encroachment during the drought. The ability to quantify the extent and severity of the encroachment problem on a statewide basis is not possible at this time due to lack of sufficient data. The drought caused a dec line in recharge which in turn lowered the potentiometric surfaces in Floridas aquifers fo llowed by a decrease in spring flow. This was exacerbated by: (1) the increased pumping of groundwater during the drought and (2) the increased demand for groundwater because of the increased population. The consequence of the drought and the increased pumping of groundwater wa s saltwater encroachment. It is indicated by decreasing trends in spring flow and increasing trends in the c oncentration of rock and saline indicators. A return of normal rainfall should greatly help in reversing the process. In the future, spring monitoring and trend analyses should identify any changes. In addition, water conservation practices, along with minimum flow s and levels (MFLs) (Florida Statutes,1983, Chapter 373.042) being established by the WMDs s hould mitigate the effect of future droughts. Nevertheless, the monitoring of population growth, pumping of groundwater, per capita water use, as well as water quality and quantity, are also needed in order to properly manage our water resources. Miscellaneous and Important Issues Falling Well Water Levels A Districtwide and Statewide Problem in Wells Well-water level trends were consistent with what was seen in spring flow. The most common single trend seen among wells was a simu ltaneous decrease in water level and pH. Trends were seen in both confined and unconf ined wells and both limestone and siliciclastic aquifers. This suggested the cause transcended lo cal aquifer or rock-matrix characteristics. A physical linkage between water level and pH can be established, at leas t for the shallow wells used in this study, by referring ag ain to Figure 57. Recall that we lls penetrate the overlying rock to the point of an intake zone marked by a we ll screen. The drought or excessive groundwater withdrawal lowered the water table in relation to the intake zone. An explanation for the drop in

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BULLETIN NO. 69 135 pH, in conjunction with the fall of the water ta ble, involves the water ch emistry near the top of the water table. Since decreases in groundwater levels prog ressively allow greater volumes of lower pH water into the well screen, this creates the obs ervationover timethat pH is dropping. Therefore, the statewide lowering in well water levels corresponds to drops in pH. Thus, the chemical and physical trends in well water during the drought may simply reflect the increasing proximity of the upper portions of the water table to the well screen. A second statewide trend observed in the shallow wells was an increase in water temperature. For Sequence A, increasing trends in temperature were observed on a statewide scale for unconfined groundwater but not for confined groundwater (Table 62). Increasing trends were evident in some districts (e.g., SRWMD) but not in others (e.g., SJRWMD and SWFWMD). There are several plausi ble explanations for the trends. The first involves the type of pumps used. Grundfos Redi-flo 2 pumps were the well pump most often used. These submersible pumps need well water to cool the pu mp motors. Samplers, particularly for large wells during sample collection, observed the wa rming of water. In comparison, peristaltic pumps were also used (e.g. for shallow wells less than 25 feet deep) and fo r springs. For these pumps, samplers did not observe altered water temperatures. It is not likely that pump heating was the ca use of increased distri ctwide and statewide temperature trends. The heating of water is not the same as the creation of an upward trend in a time series. In order for a trend to be observed, it would require not only that water be heated within the individual pump but that the amount of heat added by the pump each year increased steadily over all parts of the state Spring temperatures increased in some places but not in others. Peristaltic pumps, not submersible pumps, were used for shallow wells and springs. They do not require cooling. If well-water temperature rose as an artifact of the collection methodology then a separate explanation is needed to explain why temperat ure rose in springs, which were sampled with different equipment. Both shallow well and sp ring temperature increases were observed in the SRWMD. On the other hand, peristaltic pumps were also used in th e SWFWMD, and, as it turned out, spring-water temperatures typi cally decreased while well-water temperature increased. Another possibility is that the trends are statistical artifacts such as aliasing. Aliasing is a result of sampling over a time inte rval that is longer than the dura tion of cycles of the variable of interest. Figure 59 depicts cy clic variations of water levels The cycle is approximately 7 days in length. If sampling occurs at intervals that are less than 7 days, a cyclic pattern will be detected, even if it is not the true 7-day cycl e. By setting the sampling interval at the same period as the cyclicity, the cycles are not detected. In fact, with a 7-day cycle, the starting day of the week has a profound consequence on the apparent behavior of the data. Starting sampling on Day 1 (Monday) results in an a pparent increase in water levels over time. Starting sampling on Day 3 (Wednesday) results indicate an apparent negative trend in water levels. Clearly, there is an important relationship between the period of sampling and the pe riod of the cyclicity. This issue is important for all analytes in trend analysis since it can involve any trends. The danger is that, in a time series short enough, one limb of the false cycle can appear as an

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FLORIDA GEOLOGICAL SURVEY 136 upward or downward trending curve. The key problem with this explanation is that the results of the aliasing are cycles, not trends. As such, it is equally likely to sample in such a way that a false upward or downward trend is generated. Figure 59. Example of aliasing. Regarding water temperature, one s hould see an equal probability of up and down trends in water temperature. However, if both upwar d and downward tendencies are equally likely then it requires a second explanation to understand why trends so often tend in the same direction; or to say it another way, it is not that trends are going up but that so many are going up. The sign tests (Table 49) reveal that the majority of trends descri bed here were predominately up. The simplest explanation for increased temperature is that a single cause is responsible for the widespread singular trends. It appears that the most plausible explanati on for increasing well water temperature is an increase in air temperature. Table 67 indicates that the mean air temperature across most of Florida was about 0.29 F (0.16 C) higher during Sequence C ( 1998-2003) relative to Sequence B (1991-1997). For the shallow wells, it is possibl e that localized air te mperature increases are responsible for increasing water temperature.

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BULLETIN NO. 69 137 Nitrogen and Phosphorus NutrientsRegi onal and Local Problem in Springs Several nutrient trends in springs were anal yzed for the four water management districts providing spring data. Nitrates (in various forms), phosphorus, phosphate (or ortho-phosphate), TKN and ammonia were the most common. These can be grouped as nitrogen and phosphorus and will be addressed separately for each water management district. Nitrate concentrations have increased in nor thern Florida springs for over 30 years. The data analyzed for Wakulla Spring indicates a downward trend for the 1991 2003 time frame, yet the spring has a longer history of nitrate in creases (Figure 60). From the 1970s to the early 1990s, nitrate concentrations in Wakulla Spring rose from approximately 0.2 mg/L to over 1.0 mg/L. Increases in nitrogen trends are typica lly due to specific land use inputs. The most common inputs are from fertilizer application, septic tanks, animal excrement, golf courses, and wastewater treatment facilities (F lorida Spring Task Force, 2000). Nutrient transport is a complex process. Nitrat e and other nutrients wash into aquifers and undergo large-scale mixing with groundwat er (Martin and Gordon, 1997). Analyte concentrations in springs follo wing storms change as a functi on of epikarst (upper weathered karst) flushing. Nitrate concentratio ns increase as a result of this effect. Changes in concentration are often seasonal (Katz, 2000; Boyer et al., 1999). DateNO3 + NO2 as N (mg/L) 1/1/2005 1/1/2000 1/1/1995 1/1/1990 1/1/1985 1/1/1980 1/1/1975 1/1/1970 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 Nitrate Concentrations in Wakulla Spring(1972 2003) Figure 60. Nitrate Concentrations in Wakulla Spring between 1972 and 2005. Nitrogen in the Northwest Flor ida Water Management District One on-going study is taking place at a wastewater treatment f acility (WWTF) spray field located approximately 10 miles from Wakulla Sp ring. Wastewater has been noted to change

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FLORIDA GEOLOGICAL SURVEY 138 concentrations of a number of analytes including chloride, nitrogen, pho sphorus, organic carbon, coliform bacteria, sodium, and potassium (Elder et al., 1985). Depending on the analyte and the percent of organic material pres ent, soil and underlying rock matrices can absorb much of the material introduced. Spray-field monitoring wells have documented changes in both chloride and nitrate-nitrogen concentrati ons. Chloride has been noted to increase from 3 to 15 mg/L while nitrate-nitrogen climbed from 0.5 to 4 mg/L in nearby wells (Elder et al., 1985). The association of combined increases in nitrate and chloride has also been reported in ot her parts of the country (e.g. Ogallala Aquifer, Texas; Hudak, 2002). Weki wa Springs in the SJRWMD appear to have a similar wastewater input problem. Septic tanks are sometimes referred to as on site waste disposal systems (OSWDS). Their leachate plus lawn fertilization seem to be the most likely source of the nitrogen (Toth and Fortich, 2002). Studies of Leon and Wakulla Counties have documented six main nitrogen sources were identified: atmospheric deposition, wastewat er treatment facilities, OSWDSs, commercial fertilizers, livestock and sinking streams (Chelette et al., 2002). Of these sources, there are both inorganic and organic sources of nitrogen, either of which could be introduced in dissolved or particulate form. Forms of nitrogen can be classifi ed as either dissolved inorganic, particulate inorganic, dissolved organic, and particulate in organic. The exact contribution of each of these forms is difficult to establish. Actual amounts of nitrogen contri buted from these sources have been documented with varying accuracy. WWTF contributions are well established, whereas data from OSWDS are more difficult to acquire. Re gardless of the exact contribution, the overall contribution of WWTF a nd OSWDS comprise the majority of nitrogen inputs into the environment. They deliver, respectively, 550 and 800-2,400 kg-N/ha-yr (Chelette et al., 2002). Though atmospheric deposition of nitrogen is substantial, it is disperse d over wider areas and comprises approximately 4-5 kg-N/ha-yr (tot al of wet and dry deposition combined). Based on Chelette et al. (2002), much of the nitrogen fertilizers applied to the landscape is sequestered or returned to the atmosphere; only a fracti on becomes part of groundwater. Nitrogen is a highly reactive element and its chemi cal pathways are difficult to establish. It can be sequestered in vegetation, lake-bottom sedime nts, the subsurface, or it can return to the atmosphere. In spite of the small proportion of nitrogen actually ente ring groundwater, total nitrate discharging from Wakulla Spring at least doubled ove r the last 25 years. Agricultural sources have been documented through isotopes and water ages. Many springs have complex flow paths with older and younger flow paths converging within springs. Isotopic studies indicate a vari ety of water ages in northe rn Florida springs. Nitrate concentrations are negatively correlated to age of spring water and the nitrate originates from varying proportions of inorganic (fertilizers) and organic-N (animal wastes) sources (Katz et al., 1999b; Toth, 1999). Close correlation of nitrate trends in some Fl orida counties to county-wide fertilizer sales underscores this relationship (Chelette et al., 2 002; Katz et al., 1999b). Another factor in localization is underlying geology and soil. Even within agricultural areas nutrients may show up in groundwater in greater or less proportion based on underlying geology, soil conditions, and preferential flow pa ths within aquifers. One study in Florida illustrates this for nitrate in surface water and groundwater. In the northwestern portion of the state the Dothan soils are plenthitic (iron hard pan) with a shallow perched water table (Day,

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BULLETIN NO. 69 139 1997). These conditions result in less nitrate percolating into the aquifer, al though greater concentrations of nitrate may be concentrated in surface runoff. Other soils in the panhandle can provide a suitable environment for nitrate to persist and eventua lly find its way into groundwater. Bowman (1991) also indicated that soil types can affect nitrate input into groundwater. Our study shows that nitrate has been trending downw ard in Wakulla Spring significantly during the 1991-2003 period (Figure 60). The time series includes gaps. Howe ver, both MK trend results and WT tests of Sequence B and C data confirm a drop in the latter half of the series. These results suggest that a moderate improvement may have occurred. Loper et al. (2005) suggested that the improvements are due to decreased efflue nt concentrations at the spray field. At the same time, the highly elevated starting point of the time series in 1991 (1.0 mg/L), as compared to 0.2 mg/L in 1972, was the product of severa l decades of a strong rise (Figure 60). Nitrogen in the Suwannee River Water Management District The SRWMD was the only district to provide flow data on the days that nutrient samples were collected. This allowed an examination of flow-related loading fo r the analytes. Of the nutrient analytes examined for the SRWMD, th e only one having a distri ctwide trend was TKN (nine increased and zero decreased). At the same time, other nutrient anal ytes suggest increases and decreases. Nitrate decreased in six springs (and increased in only three), while phosphorus increased in five and phosphate increased in four (with each only decreasing in one spring). At least four explanations exist that can possi bly explain the decrease in nitrate. First, since the latter half of the time series was a drier period, it is possible that less nitrate became available to groundwater as a result of decreased precipitation or a possible reduction in fertilizer applications during the dry period. Second, dur ing the dry period, the soil may have stored nitrogen. Under both of these scenarios, when the current dry period ends, nitrate trends in springs will be expected to incr ease. Third, efforts by the local WMDs to conserve on the rates of fertilizer application were succ essful. Under this scenario, wh en the dry period ends, in all likelihood, nitrate concentra tions in springs will continue to decline. Fourth, during the drier times, spring discharge is reduced. Reduced flow creates an appearance of lower nitrate concentration in the springs. For example, fl ow-adjusted trends and flow/concentration plots revealed a different behavior between nitrate-nitrogen and T KN over the period of record. Figures 61-64 compare and contrast flow-adjusted trends. Flow adjustments were derived in two ways. The figures include plots of: (1) the product of flow volumes and nutrient concentrations against time and log-log plots of nutrient concentration as a function of the flow. The figures contrast different springs with a variety of trend directions. Troy Spring (Figure 61, top) demonstrates an inverse relationship over time fo r flow-adjusted nitrate, while the log-log plot (Figure 61, bottom) shows a positive relationship exists between nitrate concentrations (vertical axis) and flow (horizontal axis). Figure 62 (top) displays no apparent flow relationship over time for flow-adjuste d trend for TKN for Troy Spring, while Figure 62 (bottom) reveals that TKN concentration (vertical axis) has an inverse relationship with flow (horizontal axis). Figur e 63 (Hornsby Spring) shows a negativ e relationship over time for flowadjusted nitrate (top), but demonstrates a positiv e relationship regarding th e log concentration of nitrate versus the log of flow (bottom ). In Fi gure 64 (top) there is a pos itive relationship over

FLORIDA GEOLOGICAL SURVEY 144 time for TKN. However, there is a slightly negative relationship be tween the log of TKN compared to the log of flow (bottom). Hornsby Sp ring had the sharpest decr ease in flow of all SRWMD springs and actually stopped flowi ng during portions of the study period. Figures 61-64 suggest that reduced spring flow was responsible for apparent decreases in nitrate concentrations and increases in TKN concen trations. Because in all cases, whether nitrate concentration is increasing, decreasing, or showing no trend, nitrate concentrations closely follow flow amounts in the springs. This flow-depe ndent behavior is one pl ausible explanation of the decreasing nitrate trends in the Suwannee District; nitrate conc entrations may have fallen in some springs simply as a function of reduced flow. One clear observation revealed by flow adju stments is how the two forms of nitrogen differ for the SRWMD. TKN showed a clearly different pattern th an nitrate-nitrogen. For Troy Spring (Figure 61, top) nitrate loading decreased over time. However, as a function of flow, nitrate concentrations correlated positively with flow (Figure 61, bottom). On the other hand, TKN slightly increased over time (Figure 62, top), but had an inverse re lationship with flow (Figure 62, bottom). Hornsby Spring was similar to Troy Spring. Nitrat e loading (Figure 63, top) decreased over time and it correlated posit ively correlated with flow (Figure 63, bottom). TKN concentrations increased over time (Figure 64, top), but TKN had an insignificant correlation with flow (Figurer 64, bottom). As with the other two springs, nitrate loading at Fanning Spring (Figure 65, top) decreased during the drought, and nitrate concentrations were correlated positively with flow (Figure 65, bottom). With regard to TKN, its loading increased over time (Figure 66, top), and T KN was inversely correlated with flow (Figure 66, bottom). Table 69 summarizes nutrient relationships for several springs in the SRWMD. The table contains summary data for Troy, Hornsby, and Fanning Springs (already discussed), plus Little River, Telford, and Ruth/Little Sulfur (RLS) Sp rings. For each of these selected springs, the table contrasts the relationships among concentrat ion, loading, time, and flow for both nitrate and TKN. At the bottom of the table is a summary. Nitrate concentrations and nitrate loading generally decreased over time. Nitrate concentrations were positively related to flow. As flow decreased during the drought, nitr ate concentrations generally decreased. Since nitrate concentrations are dependent on flow, as rainfa ll returns to normal, nitrate concentrations may begin to increase, because of the increased spring flow. TKN behaved differently. TKN concentratio ns generally increased over time, while TKN loading generally decreased. TKN concentrations were inversely (negatively) related to flow. As flow decreased during the drought, TKN concentrations generally increased. These results raised questions concerning the different sources and chemical behaviors of both forms of nitrogen. It is clear that nitrat e closely followed the flow amountsat least for these selected springs in the Suwannee Distri ct. However, TKN shows an almost inverse relationship with flow. Since TKN is a combination of both NH3 and organic nitrogen, a possible explanation is that the sources of the or ganic nitrogen in TKN we re from either highly organic water originating from swamps or from agriculture a nd/or waste water sources.

FLORIDA GEOLOGICAL SURVEY 148 During 2003, a relatively wet year, large amou nts of organic debris, originating from swamps or other sources, possibly entered th e groundwater regime though swallets and were simply flushed through the springs. However, there is another possibi lity for increasing TKN trends. Since NH3 showed little activity in the SRWMD, changes in organic nitrogen are possibly responsible for increased trends. Orga nic material found within the deeper and older Avon Park Formation is a possibl e source of organic nitrogen a nd, by extension, TKN. During the drought, deeper organic-rich groundwater, originating from the Avon Park Formation, may have found its way to the springs. The mechanis m for transporting the olde r water to springs is analogous to that controlling the increases of ro ck and saline analyte concentrations during a drought. In either scenario, it a ppears that nitrogen from organi c sources found their way into the SRWMD groundwater during the period of record wh ile nitrate concentrat ions were controlled by spring flow. Nitrogen in the St. Johns River and Southw est Florida Water Management Districts There were no observed district wide nutrient trends in the SJRWMD. However, nutrients were a large problem in the SWFWMD. Nineteen springs showed upward tr ends in nitrate and only one had a downward trend. In compar ison, phosphorus and phosphate trends (to be discussed shortly) were suggestiv e of a slight improvement. Unlike the SRWMD, flow data were sparse for the SWFWMD and loading could not be determined. This disparity (dominant upward trends in SWFWMD for nitrate but relatively inactive [or improving] phosphorus trends) provided another good example of the patchy nature of nutrient tr ends in the state. Much has been said about the SWFWMDs nitrate problems (C hampion and DeWitt, 2000; Champion and Starks, 2001; Jones and Upchurch, 1994; Jones et al., 1996; Jones et al., 1997). These earlier works provide explanations for what is seen in this study. The following springs had upward nitrate trends during th e period of record: Boat, Buckhorn Main, Chassahowitzka No. 1, Chassahowitzka Main, Hidden River Head, Hidden River No. 2, Homosassa (Nos. 1, 2 and 3), Hunter, Magnolia, Pumphouse, Rainbow (No. 1 and 6), Rainbow Bridge Seep, Salt, Tarpon Hole, Trotte r Main, and Weeki W achee Main Springs. Marion County Marion County includes the Rainbow Springs Group; the fourth largest spring group system in Florida. Data were analyzed for Rainbow No. 1, Ra inbow No. 4, Rainbow No. 6, Rainbow Swamp No. 3, and Rainbow Bridge Seep. Rainbow Springs Group Rainbow Springs Group, like many other springs in the SWFWMD, had nitrate concentrations well above that of the natural Floridan aquifer system value (<0.05 mg/L). The main source of nitrate in the group was primarily derived from inorganic s ources of nitrate, in particular inorganic fertilizers a pplied to pastures near the springs Thus the nitrates represent a local flow system (Champion and Starks, 2001; Jones, et al., 1996).

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BULLETIN NO. 69 149 Citrus County Citrus County has several spring groups: Kings Bay, Homosassa, and Chassahowitzka Springs Groups. Springs included Chassahowitz ka No. 1, Chassahowitzka Main, Hidden River Head, Hidden River No. 2, Homosassa Numbers 1-3, Hunter, Pumphouse, and Trotter Main Springs. Kings Bay Springs Group The Kings Bay Springs Group is the second larg est system in Florida. Tarpon Hole and Hunter Springs are part of this group. Freshwater springs were locat ed on the east side of the bay while springs with brackish wate r were found in the central a nd western portions. As of 2001, flow in the springs was only 75 percent of the historical average (C hampion and Starks, 2001). Water quality in the Kings Bay Springs Gr oup is tidally influenced. TDS and chloride concentrations change with tides This suggests that, even at lo w tide, the springs are strongly influenced by the coastal transition zone. Most nitrate input was from inorganic sources, most likely inorganic fertilizers applie d to golf courses and residential properties near the springs. Thus, the nitrates are indicative of a local flow system (Jones and Upchurch, 1994). Homosassa Springs Group The Homosassa Springs Group, in western Ci trus County, had several springs with upward nitrate trends: Homosassa Trotter Main, Pumphouse, and Hidden River Head. Like the Kings Bay Group, the Homosassa Springs Group show s an influence from the coastal transition zone (Jones et al., 1997). Like the Kings Bay Springs Group, Ho mosassa Springs Group nitrates were derived primarily from inorganic sources of nitrateinorganic fe rtilizers applied to residential and golf course turf grass near the springs. Again, the nitrates represent a local flow system. Chassahowitzka Springs Group Like the Kings Bay and Homosassa Groups, Chassahowitzka Springs Group varies between fresh and brackish and is tidally influenced. TDS and chloride concentrations varied greatly, showing a coastal transition zone influen ce even at low tide (Jones et al., 1997). Nitrate concentrations were generally below 0.6 mg/L but varied among individual springs in the group. Mixing of coastal transition zone waters and variations in Floridan aquifer system nitrate concentrations were sources of variations. Most nitrate was derived from i norganic sources, such as inorganic fertilizers applied to residential and golf c ourse grass near the sp rings (Jones et al., 1997). Hernando County Hernando County included two spring group s: Weeki Wachee and Aripeka Springs Groups. Springs included Boat, Ma gnolia, Salt, an d Weeki Wachee.

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FLORIDA GEOLOGICAL SURVEY 150 Weeki Wachee Springs Group This group lies within western Hernando County, southwest of Brooksville and is located inland of the brackish water to the west. Week i Wachee Main Spring had increasing nitrates. As with other SWFWMD springs the sources of nitrate are probab ly inorganic fertilizers applied to golf and residential lawns in the vicinity of the springs (Jones, et al., 1997). Boat Springs, Bobhill, and Magnolia Springs These springs are located southwest of th e Weeki Wachee Springs Group in Hernando County. Average discharge for thes e springs is relativel y low (Rosenau, et al., 1977). As with other SWFWMD springs, TDS and ch loride concentrations range from fresh to brackish with proximity to the coast. TDS and chloride concen tration changes suggest the group is influenced by the coastal transition zone. The sources of nitrat es are possibly inorganic fertilizers applied to residential and golf course lawns near the springs. Hillsborough County The only sampled springs in Hillsborough County were Lithia Spring and Buckhorn Springs. The only spring with increasing nitrate was Buckhorn Spring. Lithia Spring and Buckhorn Spring Unlike most of the other springs, Lithia and Buckhorn Springs exhibit little change in TDS or chloride. They are not affected by the higher salinities of the transition zone. The high amounts of nitrate in Lithia and Buckhorn Spri ngs are derived from an inorganic source inorganic fertilizers applied to citrus within the vicinity of the springs (Jones and Upchurch, 1994). Summary of the Nitrate Problem in Spring Water Originally, the land around th ese springs consisted of pine forest, hammock forests and scrub (Champion and Starks, 2001; and Wolfe, 1990). This natural setting was eventually replaced by agricultural deve lopment such as livestock pastures, row crops and citrus. Additionally, the last several decades have included urban and commercial development. These developments included many residential units and golf courses. Studies at the SWFWMD have concluded that during the last 25 years, nitrate from inorganic fe rtilizers has leached into the Upper Floridan aquifer and is now dischargi ng from the springs. Popul ation within SWFWMD has been projected to increase to 4.6 million by 2010 (Champion and Starks, 2001). With nitrate already leaching into th e FAS, and development ongoing, the ni trate increases wi ll continue for the foreseeable future. Phosphorus in Spring Water by Water Management District Phosphorus is strongly correlated with underlyi ng phosphatic rock formations in Florida, predominately from the Hawthorn Group (Scott et al., 1991). The unusually high phosphorus

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BULLETIN NO. 69 151 contents of streams and lakes deriving water drained from phosphatic areas have long been studied (Odum, 1953). Other potential sources of increased phos phorus in springs involve industry and wastewater. Naturally high phosphorus concentrations occur in surface waters in some parts of the state, but can be elevated in other areas by municipal wastewat er and phosphate mining. Because the removal of phosphorus is not often a ddressed in wastewater treatment, it is an important source of contamination. Although some facilities may have the ability to treat for phosphorus, most onsite wastewater treatment and sewage treatment faci lities do not prevent introduction of phosphorus into the environment. Suwannee River Water Ma nagement District Wakulla Spring is the only spring that was evaluated in the NWFW MD and for Wakulla Spring, phosphorus was not an issue. For the SR WMD, flow-adjusted tr ends for phosphorus and phosphate were examined. Figu res 67-75 compare flow-adjuste d trends among springs that show varying trends in phosphorus and phosphate. Overall, the response of phosphate is more similar to that of TKN than nitrate-nitrogen for the SRWMD. Figures 67 and 68 are examples of the relationship between flow and analyte concen trations in a spring (Troy) for phosphorus and phosphate. Time series of the flow-adjusted anal ytes show little eviden ce of temporal trends (Figures 67, top and 68, top). Log-log plots of concentration and flow (Figures 67, and 68, bottom) show only slight rela tionship between: (a) flow and phosphorus, or (b) flow and phosphate concentrations. Ruth/Little Sulfur (RLS) Spring shows a sli ght decrease in the log of concentration versus the log of flow (Figures 69, top and 70, top) for both analyt es. However, it has slightly decreasing phosphorus and phosphate flow-adjusted trends over the period of record (Figures 69, bottom and 70, bottom). Fanning Spring (Figures 71 a nd 72) shows a slightly different picture. Flow-adjusted concentrations for both phosphoru s and phosphate decrease after 1998 [(Figures 71 (top) and 72 (top)]. However, phosphorus concen trations increase w ith flow (Figure 71 bottom), while phosphate concentrations decrease s lightly over time (Figure 72, bottom). Little River Spring (Figure 73) has decreasing phosphorus and phosphate flow-adj usted trends over the period of record (Figures 73, t op and 74 top). The log of phos phorous and the log of phosphate (Figure 73 bottom and 74, bottom) both decrease with the log of flow. However, like TKN, both phosphorous and phospha te also showed nega tive relationships between the log of the concentration and the log of the flow. An explana tion for these trends is suggested when these plots are compared to one of the few examples of a decreasing phosphate trend in the SRWMD. Hornsby Spring showed a strong decrease in flow-adjusted phosphate (Figure 75, top), with an increa se at the end of the time se ries. The strong downward trend reflects the rapid reduction in flow within Hornsby Spring over the ti me series. A log-log plot of concentration against flow (Figure 75, bottom) shows a positive increase, unlike the other springs. When phosphate decreased, flow also decr eased. The implications are that, like TKN, phosphorus-based nutrients increased at a rate fast er than flow decreased. This is why trends

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FLORIDA GEOLOGICAL SURVEY 152 Figure 67. Flow adjustment for phosphorus in Troy Spring phosphorus (top) show little declines over time while the log of phosphorus has a negative relationship to the log of flow. Phosphate (botto m) shows a slight negative trend over time while the log of phosphate has little to no relationship to the log of flow. 102 6789Flow (cfs) 3 4 5 6T-Phosphorus (mg/L) [x 10-2] 5/1/19989/13/19991/25/20016/9/2002 Date 5 15 25 35Flow (cfs) P (mg/L) Troy: Flow-Adjusted Phosphorus

FLORIDA GEOLOGICAL SURVEY 160 Figure 75. Flow adjustment for phosphate in Hornsby Spring. One of the few examples of a decreasing phosphate trend in the SRWMD. Flowadjusted phosphate shows a pronounced d ecline over time with a large increase at the end (top). The log of phosphate as a function of the log of flow (bottom) shows an association. This pattern is the opposite of what is seen with the majority of the SRWMD springs where increasing phosphate tr ends correspond to a negative relationship with the log of flow. 1/1/199711/14/19989/27/20008/10/20026/23/2004 Date 0 50 100 150 200Flow (cfs) o-PO4 (mg/L) Hornsby: Flow-Adjusted Phosphate 10-1.0100.0101.0102.0 23456234562345623456Log Flow (cfs) 10-1.0 7 8 9 2Log o-PO4 (mg/L)

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BULLETIN NO. 69 161 with decreasing concentrations (like phosphate at Hornsby Spring) show positive relationships with flow: the concentrations were almost en tirely dependent on flow, and the concentrations were decreasing. A reduction in flow may have actually masked a number of otherwise upward trends in nutrient analyte concentrations. This would mean that the actual number of nutrient increases may be greater than this report is able to document and it is likely the trends recorded here underestimate the true number of increases. A second explanation for reduction in phosphate has been noted in other states. Trend analyses in water quality of North Carolina no ted a significant reduction in phosphate following the 1988 state-wide ban of phosphate use in deterg ents. Trend analyses s how reductions from the time period of 1983 to 1995 (Childress et al., 1998). Similar reductions in phosphate detergent, or improvements in wastewater treatment, coul d also result in downward phosphorus trends in Florida. The most plausible explanation we can postula te includes a hypothesi s that explains the selective nutrients, plus rock and saline analyte trends. TKN and phosphorus-based nutrients increased at a rate faster than flow decreased. The phosphorus tr ends may simply be additional observations of the shrinking of Floridas fres hwater lens and the uptake of older water inferred across the state. Several seemingly unr elated trends (e.g. salinity, pH, phosphorus) are simultaneously answered by this single explanat ion making it the preferre d, but not necessarily the correct, option. More work is need ed to fully understand this observation. St. Johns River and Southwest Fl orida Water Management Districts The SJRWMD had no increasing phosphate tre nds with 11 decreasing trends, while the SWFWMD had no increasing trends w ith five decreasing trends. Po ssibly related to this is the observation that the SJRWMD also witnessed nine springs showing significantly increasing pH values, with only one spring show ing a decrease. Odum (1953) obs erved that surface waters in Florida, such as streams, often have high conc entrations of phosphorus a nd low pH values. On the other hand, we observed that springs have hi gh pH values, relative to surface waters, and often contain less phosphorus conc entrations than streams. Odum (1953) suggested a controlling role for pH in the solubility of phosphorus in natural surface water c onditions. Based on these observations, the decreasing trends observed for phosphate and phosphorus may actually reflect an increasingly larger volume of deeper water components comprising spring-water because of the drought. Such deeper water would be both hi gher in pH and lower in phosphorus. With the exception of the SRWMD, nearly every phosphorus-related trend in the state is downward. This explanation has the advantage of being consistent with the clearly observed statewide increase in rock and saline indicators. Thus, if older and deep er-sourced water is disc harging at springs, then it would create both a strong increase in rock and sali nity trends, which are clearly documented, as well as the decrease in phosphorus seen here.

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FLORIDA GEOLOGICAL SURVEY 162 Comparison of Coastal to Inland and Tidal to Non-Tidal Springs Most trends observed in this study were for rock-matrix and saline analytes and most were caused by the drought. By closely examining the trends displayed in this report, it became obvious that the magnitude of change for spring s located near the coas t during the drought was greater than for inland springs. However, did coas tal springs have proporti onally more increasing trends than did inland sp rings? Did tidal springs have propor tionally more increasing trends than did non-tidal springs? An inspection of Figures 13, 16, 27, and 32 reveals that for some spring, it is easy to determine as to whether they are in land or not. Others are not so ea sy to identify. For example, in the SJRWMD, almost all springs in this report are lo cated very near the St Johns River, which parallels the coast (Figure 27). For this reason, SJRWMD spri ngs were not used in this evaluation. Wakulla Spring in the NWFWMD (Figure 13) is lo cated near the coast and was easily categorized as being a coastal spring. For the SRWMD, the Suwannee River flows roughly perpendicular to the coast (Figure 16 ). Based on this observation, the authors categorized the first seven spri ngs, beginning at the mouth of the Suwannee River as being coastal. All other SRWMD springs were placed into the inland category. Staff at the SWFWMD categorized their spri ngs for us. The spring categorizations for both WMDs are found in Table 70. Table 70. Inland and Coastal Springs within the SRWMD and the SWFWMD SRWMD (including Wakulla Spring) SWFWMD Coastal Springs Inland Springs Coastal Springs Inland Springs MAN ALR Betty Jay Bobhill FAN LBS Boat Boyette HAR TEL Chassahowitzka No. 1 Bubbling RKB SBL Chassahowitzka Main Buckhorn LRS ROY Hidden River Head Catfish RLS GIL Blue Hidden River No. 2 Lithia TRY POE Homosassa No.1 Rainbow No. 1 Wakulla (NWFWMD) HOR Homo sassa No.2 Rainbow No. 4 Homosassa No.3 Rainbow No. 6 Hunters Rainbow Swamp No. 3 Magnolia Rainbow Bridge Seep Pump House Weeki Wachee Main Salt Wilson Head Tarpon Hole Trotter Main Once the springs were categorized, a two-sa mple proportion test (Sullivan, 2004) was used to determine whether the pr oportion of springs w ith upward trends was the same for both coastal and inland springs. Data from Sequence C were used. Each test was conducted for each of the rock-matrix and the saline indicators at a significance level of 0.05. The null hypothesis

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BULLETIN NO. 69 163 was that the proportions of upwar d trends were the same for bot h coastal and inland springs, while the alternate hypothesis was th at they were not the same. The results are found in Table 71. The table li sts the analyte in the first column. The second, third, and fourth columns contain the nu mber of coastal springs trending upward, the number trending downward and th e proportion of springs trending upward for coastal springs. Columns five, six, and seven lists the number of inland springs trending upward, the number trending downward and the proportion of springs tr ending upward for inland springs. Finally, the right-hand column (column 8) displa ys the p-values for each test. All of the p-values are greater than 0.05. Based on this ev aluation, there are insufficient data to conclude that the propor tion of coastal springs were diffe rent from inland springs during Sequence C. For the springs showing trends for the rock-matrix and saline analytes, greater than 90% of the trends were increasing. This was true regardless of be ing associated with coastal or inland springs. Table 71. Comparison of Coastal and Inland Springs for Upward Trends During Sequence C, excluding spring in the SJRWMD Analyte Coastal U Coastal D Prop C UInland U Inland DProp I U P-value Alk 13 0 1.000 12 2 0.857 0.488 Ca 16 0 1.000 17 0 1.000 1.000 Mg 20 0 1.000 18 0 1.000 1.000 Cl 14 1 0.933 15 2 0.882 1.000 F 1 0 1.000 5 0 1.000 1.000 K 15 1 0.938 10 0 1.000 1.000 Na 19 0 1.000 18 1 1.000 1.000 P 9 2 0.812 5 3 0.625 0.603 PO4 8 0 1.000 3 1 0.750 0.333 SC 14 5 0.736 15 2 0.882 0.408 SO4 11 3 0.786 14 2 0.875 0.642 I = Inland, C = Coastal The results of Table 71 repres ent a geographic comparison (coa stal versus inland). Some individuals at the SWFWMD expressed a concern th at not all coastal springs listed in Table 70 were tidally influenced. They requested a compar ison of tidal versus non-tidal springs. The two right-hand columns in Table 70 represent coasta l and inland springs in the SWFWMD. All of their coastal springs are tidally influenced, wher eas their inland springs are not. Data from the springs listed in the two right -hand columns of Table 70 were used to produce Table 72. The results in Table 72 list the analytes in th e first column. The second, third, and fourth columns contain the number of tidal springs trending upward, the number trending downward and the proportion of springs trending upward for tidally-influenced spri ngs. Columns five, six, and seven lists the number of non-tidal springs trending upward, the num ber trending downward and the proportion of springs trending upward for non-tidally in fluenced springs. Finally, the right-hand column (column 8) displa ys the p-values for each test.

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FLORIDA GEOLOGICAL SURVEY 164 Table 72. Comparison of Tidal and Non-Tidal Springs for Upward Trends During Sequence C in the SWFWMD Tidal U Tidal D Prop T U Non-Tidal U Non-Tidal D Prop Non-Tidal U P-Val Bicarb 12 0 1.000 9 0 1.000 1.000 Ca 6 0 1.000 3 0 1.000 1.000 Mg 8 0 1.000 6 0 1.000 1.000 Cl 6 0 1.000 6 1 0.857 0.857 F 1 0 1.000 3 0 1.000 1.000 K 7 0 1.000 8 0 1.000 1.000 Na 6 0 1.000 8 0 1.000 1.000 P 1 2 0.333 0 3 0.000 1.000 SC 7 0 1.000 5 0 1.000 1.000 S04 8 0 1.000 4 0 1.000 1.000 Sr 10 0 1.000 9 0 1.000 1.000 TDS 4 0 1.000 6 0 1.000 1.000 Note that all of the p-values listed in Ta ble 72 are greater than 0.05. Since many of the tidal springs in Table 72 are the same as the coas tal springs listed in Tabl e 70, it is not surprising that the results in Table 71 and Ta ble 72 are similar. Note that the sample size is small. Note also that unlike the other analytes, phosphorous had decreasing trends. In spite of phosphorous, based on this evaluation, there is insufficient data to conclude that the proportion of upward trends for tidal springs were different from non-tid al springs. For the springs showing trends in the rock-matrix and saline analytes, greater than 90% of the trends were increasing. This was true regardless of being associated with tidal or non-tidal springs. Global Factors Influencing Floridas Groundwater Reasons for the trends in Floridas groundwat er may range from small-area (large-scale) to large-area (small-scale). For those utilizing Floridas resources, severa l large-area influences need to be discussed. Global Long-Term Cycles: Atlantic Multidecadal Oscillation The Atlantic Multidecadal Oscillation (AMO) is a term used to describe long-term changes in sea surface temperature (SST) of the No rth Atlantic Ocean. Cycles of cool and warm ocean temperatures are quasi-periodic lasti ng between 60-80 years (Kerr, 2000, 2005). The AMO is driven by ocean-scale changes in the Atlantic, most likely associated with thermohaline circulation. For Florida, these changes have been observed to be particularly strong (Sutton and Hodson, 2005). An AMO warm phase delivers more precipitation, while a cool phase may be marked by drought. For southern Florida, inflow into Lake Okeechobee can change by 40 percent between extremes (Figure 76, top). It s hould be noted that a similar observation between the AMO and surface water-flows in the SWFW MD have been observe d (Southwest Florida Water Management District, 2004). Figure 76 (top) displays change s in North Atlantic SST as a function of time. The period prior to 1920 had relatively low temperatures Between 1920 and 1960 the SST increased. It decreased from 1960 to about 1970, and then subse quently it rose again. The effects of the

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BULLETIN NO. 69 165 Figure 76. Atlantic Multidecadal Oscillation and Florida spring flow. The Atlantic Multidecadal Oscillation (AMO, top panels) compared to long-term changes in Florida's sp ring flow (bottom). Top show s North Atlantic sea surface temperature (SST, C) since 1900. Top lower panel shows effects of the positive AMO on the rainfall and correspondin g flow into Lake Okeechobee. Bottom chart is the log of flow against time for two large Florida springs: Silver Springs and Weeki Wachee Springs. The lines (smoothed spring flow) increase until 1960 (marked) and decline thereafter. Flow from the springs align with AMO patterns during past century. (National Oceanic and Atmospheric Administration [2006b]).

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FLORIDA GEOLOGICAL SURVEY 166 positive AMO were reflected in southern Florida rainfall and inflow into Lake Okeechobee. Figure 76 (bottom) shows spring flow for Silver and Weeki Wachee Springs, two major springs in Florida with long term flow da ta. It shows the log of flow over time. A semi-arbitrary line, drawn at 1960, marks a divide between a period of relative increases in spring flow and subsequent declines. The dividing line closely corresponds to AMO patterns, sugges ting this is a strong influence for Florida springs. AMO cycles are influenced by other oceanogr aphic anomalies (McC abe et al., 2004). More than half of the spatia l and temporal variance of th e multidecadal drought frequency over the conterminous US is related to the Pacifi c Decadal Oscillation (PDO) and AMO together. These droughts also influenced Floridas groundwater. Kerr (2000, 2005) indicates that the recent drought impacts over the United States (1996, 1999-2002) were associated with North Atlantic warming (positive PDO) and northeastern and tropical Pacific cooling (negative PDO). It is believed that the positive AMO since 1995 (i.e., warm North Atlantic SST) may continue. Because of this, changes in the PDO have important implications for the state of Florida. In mid1998, the PDO became negative until 2002 when both PDO and AMO became positive. A positive AMO and a negative PDO (e.g., 1998) can result in a drought similar to that suffered by Florida in the 1950s. However, a positive AMO and a positive PDO can also cause a drought (e.g., the drought Florida went through in the 1930s ). Thus, if the PDO remains positive while the AMO continues to be positive, a decade-long 1930s-type drought is a possibility (McCabe et al., 2004). The authors indicated this has important impli cations for water resource planners, particularly in the more arid southwestern portions of the US. At the same time, results of analyses in this report show a clear affect on Florida groundwater by the same climaticallydriven process. Global Short-Term Cycles: El Nio and La Nia In addition to the longer-term global change s seen in the AMO and PDO the time period encompassed two additional significant events: back -to-back years of an extreme El Nio and an extreme La Nia. For background, El Nio is an oscillation of tropical Pacific oceanatmospheric interactions. The usual effects of El Nio are increased rainfall and flooding or drought and wildfirevarying depending on loca tion around the Pacific Basin. Under normal conditions, trade winds blow west ward across the tropical Pacific, pushing back the warmer overlying surface water (Figure 77, middle panel). Th is creates a slightly higher sea surface in the western (compared to the eastern) Pacific. The temperature in the western Pacific can also be about 8C warmer than the eastern. This allows c ooler, nutrient-rich deeper water off the coast of South America to upwell. Rainfall is commonly less over the cooler east ern waters during this period. However, during El Nio, trade winds are re duced and there is a decrease in the depth of the thermocline in the western Pacific. Warmer water then moves east and caps the cooler, normally upwelling water, in the east. This crea tes a band of warm water across the Equatorial Pacific (Figure 77, bottom panel). As a result, more rainfall and flooding occur in places such as Peru. La Nia is something of a reverse of El Nio. It is charact erized by atypically cold water temperatures in the Equatorial Pacific (compare d to the warm water characterizing El Nio). A band of cold water is observed to stretch along the Equator during La Nia (Figure 77, top panel). El Nio and La Nia ar e the opposite ends of the El Ni o-Southern Oscillation (ENSO) cycle. El Nio is sometimes the warm phase of ENSO while La Nia is the cold phase.

FLORIDA GEOLOGICAL SURVEY 168 Without respect to this knowledge, this study was broken into time sequences that reflected the timing of the events: Sequence B (1991-1997) ended with El Nio and Sequence C (1998-2003) began with La Nia. Analysis of h undreds of individual time series bridging these time sequences revealed that 1998 was a visible br eak-point in the data, analogous in geology to a stratigraphic marker bed. This means that data from various sp rings and wells could sometimes be referred to common visible time series excursions ar ound that approximate period of time. This raises the possibility th at, although Florida was under the influence of a longer-term decline in water quantity (Figure 77), the cons equence of these shorter-duration perturbations were more strongly felt. Brief but substantial excursions in anal yte values whether upward or downward probably contribute a greater influence on the overall trend lines than do more subtle, long-term influences. Thus, excursions in 1997-1998 and dr ought are likely the cause behind most of the trends in this report. Earlier years of the study included a weak La Nia (1994-1995). This was followed by a very strong El Nio, occurring in 1997. Immediately following this was a strong La Nia (cold) event in 1998. These extreme years were followed a severe statewide (and national) drought in 2000. Acid Rain One possible explanation for the decrease in well-water pH over the study period was acid rain. Acid rain is often the product of sulfur, carbon, or nitrogen oxide s that result from industry, burning coal, or combustion of other materials. During the investigation, it was suggested that lower well-water pH values si mply reflected increasing airborne chemical pollutants in Floridas precipitation. If this were true a time series of pH values in Florida rainfall should show a decreasing trend. Figure 78 reveal s that this was not the case. The figure plots the mean monthly rainfall pH values for seven rainfall stations from around Florida (Appendix M). The rainfall means showed no significant trends over time, though standard deviation decreased slightly. The drought resu lted in less rainfall. This should result in a reduction in the pH standard deviation, not an increase. Implications of Future Low Rainfa ll and Increasing State Water Demands The AMO cycle seen in Figure 76 is approx imately a 60-year cycle with 30 years of increased rainfall followed by 30 years of decrease d rainfall. Since little is known about these cycles, the accurate modeling of future rainfall ch anges is not currently possible. At the same time, with a state that is growing so rapidly in population as Florida, water demand increases are inevitable. Regardless of current lack of ability to understand larger-scale driving factors in water quantity, the influence on statewide water res ources created by AMO/PDO and El Nio/La Nia may soon prove to be important. For the sake of illustration, a simple scenario can be posited. If one can assume a cycle is 60-years long (something which cannot be predicte d in advance) and one can assume that the increase began in 2004, this would mean a welcomed 30-year increase in rainfall. At the current rate of growth of more than 700 people per day, an increased volume of wa ter would relieve state water needs and possibly reduce or reverse incr easing concentrations of both rock and salineindicators in spring water. However, once the cy cle reached its high point, a decline in rainfall

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BULLETIN NO. 69 169 2/12/199011/8/19928/5/1995 5/1/19981/25/200110/22/2003 Date 4.4 4.6 4.8 5.0 5.2Mean pH (s.u.) Average Meteoric pHAverage From Seven Statewide Stations Figure 78. Average monthly pH from seven atmospheric rain stations (19912003). will follow for the next 30 years. The concern is that Florida would no l onger have its current 18 million residents, but millions more. By 2010, it is estimated that the population will be over 19 million and, by 2030, it will be 29 million (Clous er, 2006; McGovern, 2004). Once rainfall declines begin, the amount of recharge will be less, and because of Floridas increased population, the demand for groundwater will increase. Floridas springs can be expected to have substantially lower amounts of flow, and, unless appropriate, long-term su stainability measures are incorporated into public policy, th e quality of spring water will decline. Implications Regarding Long-Term Sustainability Alley et al. (1999) stated that groundwater sustainability is the development and use of groundwater in a manner that can be maintain ed for an indefinite time without causing unacceptable environmental, economic or social c onsequences. Scott (2001) estimated that more than two quadrillion gallons of potable groundwater exist within Floridas aquifer. They also believed that in order to determine the outlook for sustaining Florida s groundwater resources, four questions needed to be addressed: What is the level of infrastructu re development and population growth that is supportabl e by the states water resources? Should mineralized waters be consider ed as part of a sustainable water supply? How much impact on the e nvironment is acceptable? How do we balance ecological sustai nability with human needs and economic growth?

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FLORIDA GEOLOGICAL SURVEY 170 Scott (2001) also indicated that once the removal of water exceeds the recharge, mining of the groundwater occurs. At that point, Floridas groundwater is no longer sustainable. With Floridas growing population, what are reasonable solutions? Scott and Schmidt (2000) mentioned that mineralized water can be converted to fresh water through reverse osmosis (RO) processes and surface water can be used to supplement groundwater supplies. However, they pointed out that both potential solutions present their own set of problems and they proposed a set of subsequent questions: Does the inclusion of these waters in the sustainable supply create a false sense of security? Should aquifer storage and recovery (ASR) water be a portion of the sustainable water supply? Should growth management and e nvironmental stability rely on RO and ASR waters? Is it wise to allow growth management and environmental decisions to be based on expensive altern ative water supplies or is that simply avoiding the natural limitations? These are very serious questions that the citizens of Florida will face in the very near future. Analyses from this report suggest that salt-water encroachment may already be occurring and as our population con tinues to grow, we are mo re susceptible than ever to droughts. We need to commence addressing these issues now. If the AMO theory is correct, we may be fortunate and have a 30-year wet period in store for us. If so, we may have additional time to address the sustainability issue. If it is incorrect, we need to address the issue now.

BULLETIN NO. 69 183 APPENDIX B. GLOSSARY OF TER MS AND POSSIBLE CAUSES OF TRENDS APPENDIX B1. GLOSSARY (Modified from Poucher and Copeland, 2006) alluvial sinkhole An alluvial sinkhole is an ancient or relict sinkhole (paleosinkhole) that has been filled with soil and/or sediment. It may or may not have a surficial expression. See also paleosinkhole and relict sinkhole (SDII Global Corporation, 2002). artesian A modifier that describes a condition in wh ich the potentiometric surface is above the elevation of the top of the aquifer (Modified from Field, 1999). It is synonymous with confined aquifer A body of soil, sediment, or rock that is satur ated with water and sufficiently permeable to allow production of water from wells (SDII Global Corporation, 2002). blind valley A stream valley that terminates abruptly at a sinkhole, swallow hole, or swallet (where the stream disappears underground) (SDII Global Corporation, 2002). caliche See duricrust cave A natural underground opening or series of openi ngs and passages large enough to be entered by an adult person (Modified from Monroe, 1970). cavern A cave or conduit system with larger than average size that has been cr eated by the dissolution of limestone or other soluble rock (SDII Global Corporation, 2002). cavernous porosity A pore system having large, cavernous openings; the lower size limit, for field analysis, is practically set at approximately th e smallest opening that an adult person may enter (Field, 1999). "chimney" sink A cover-collapse sinkhole that forms near a vertical shaft or chimney, typically developing where bedrock is near land surface. These features are common in the Gainesville area of Florida (Modified from SDII Global Corporation, 2002). collapse sinkhole A type of sinkhole formed by collapse of the cover materials (soil, sediment, or rock) into an underground void created by the dissolution of limestone or dolostone. See rockcollapse sinkhole and cover-collapse sinkhole (SDII Global Corporation, 2002). conduit; karst conduit Large dissolutional voids, including enlarged fissures and tabular tunnels. In some usage, it is restricted to voids that are water-filled. Conduits may include all voids greater than 10 mm (one cm) in diameter, but another classification scheme places them between arbitrary limits of 100 mm to 10 m. Whichever valu e is accepted in a particular context, smaller voids are commonly termed subconduits (Field, 1999). conduit flow; karst conduit flow Undergroundwater flow within c onduits. Conduit flow is generally turbulent, but can also be laminar (Field, 1999). confined See artesian.

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FLORIDA GEOLOGICAL SURVEY 184cover Materials consisting of soil, sediment, or rock that overlies the soluble rock (limestone, dolostone etc.) in a karst terrane. In Florida, the cover includes the sand and clay deposits that overlie the limestone (Modified from SDII Global Corporation, 2002). cover-collapse sinkhole A sinkhole formed by cover materials (sand, clay, etc.) raveling into a void in the underlying limestone (Modified from SDII Global Corporation, 2002). cover-subsidence sinkhole A collapse sinkhole that forms when the upper surface of the limestone is dissolved away, and the cover materials slowly subside to occupy the space once occupied by limestone. Voids may not be well developed in cover-subsidence sinkholes because of the continued downward movement of cover materials. See also solution sinkhole and sag depressions (SDII Global Corporation, 2002). diffuse flow Groundwater flow conditions that are genera lly slow-moving, may be laminar (Reynolds number much less than 1.0), has uniform discharge, and a slow response to storms (Modified from Field, 1999). discharge The rate of flow at a given instant in terms of volume per unit of time (Modified from Neudendorf et al., 2005). It is synonymous with flux. doline A bowlor funnel-shaped hollow in limestone topography, ranging in diameter from few meters to a kilometer, and in depth up to sever al hundred meters (Modified from Monroe, 1970). A doline is synonymous with sinkhole dolostone A sedimentary rock composed predominantly of the mineral dolomite (Ca,Mg(CO3)2). While soluble, dolostone is less likely to contain well-developed karst features than limestone (Modified from SDII Global Corporation, 2002). duricrust A deposit of precipitated minerals, mainly calcite formed in the soil or near-surface layers in arid or semi-arid zones at the horizon where a scendant capillary water evaporates and salts held in solution are deposited. In Florida, seasonal ra infall and intense evaporation may form similar semi-concreted soils within the epikarst (Modified from Field, 1999). epikarst 1 The zone of weathering that penetrates the upper surface of a limestone stratum. Weathering of limestone results in development of rubble, fine-grained, carbonate-rich silt, clay, and karren (including pinnacles and valleys in th e limestone rock surface) (Modified from SDII Global Corporation, 2002). 2 An intensely dissolved zone consisting of an intricate network of intersecting roofless, dissolution-widened fissu res, cavities, and tubes dissolved into the uppermost part of the carbonate bedrock. The dissolution features in the epikarst zone are organized to move infiltrating water laterally to down-gradient seeps and springs or to collector st ructures such as shafts that conduct the water farther into the subsurface (Huntoon, 1995). estavelle 1 A spring that reverses flow because of relative changes in the elevation of groundwater potentials and stream stage (SD II Global Corporation, 2002). 2 An intermittent spring resurgence or exsurgence, active only in wet seas ons (Modified from Field, 1999). Generally, an estavelle is located near streams or rivers. When the water level of the stream is high (e.g. during flood stage), surface water directly recharges the aquifer. exsurgence A spring or seep in karstic terrane not clearly connected with swallets (or ponors ) at a

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BULLETIN NO. 69 185 higher level (Field, 1999). fissure Any discontinuity within the rock mass that is either initially open or capable of being opened by dissolution to provide a route for water movement. Fissures in this sense, applied generally in karst, therefore include the primary sedimentary bedding planes as well as tectonic faults and joints. More specifically, the term has been used to describ e voids with an average width dimension of 10 to 100 mm (Modified from Field, 1999). fracture Cracks formed in soils, sediment or rocks by natural stresses. In Florida, many fractures have been developed to relieve stress caused by Earth tides (SDII Globa l Corporation, 2002). It is synonymous with joint fracture trace A confirmed pattern observed through remote sensing (areal photography or satellite imagery) that owes its origin to jointing or fr acturing in the underlying soils, sediments, or bedrock. See photolineament (SDII Global Corporation, 2002). grotto A cave chamber or room preceded by a narrower passage (Modified from Field, 1999). joint See fracture. karren Features that develop on the upper surface of a lim estone or other soluble rock as it is weathered These features are prevalent in the Quilin area in China and in western Ireland. In Ireland they are sometimes referred to as burren. In Flor ida, karren are usually buried under the cover materials and consists of pinnacles and depressions in the rock surface. The depressions may or may not be related to sinkhole activity (M odified from SDII Global Corporation, 2002). karst A term describing landforms that have been modifi ed by dissolution of soluble rock (limestone or dolostone) (Modified from SDII Global Corporation, 2002). karst terrane A terrane, generally underlai n by limestone or dolostone, in which the topography is chiefly formed by the dissolution of rocks, a nd which may be characterized by sinkholes, sinking streams, closed depressions, subterranean drainage, and caves (Copeland, 2003). karst window 1 A depression opening that reveals portions of a subterranean flow, or the unroofed portion of a cave (a vertical window). 2 An opening in natural limestone walls formed by the joining of subterranean karst grottos as a resu lt of dissolution processes (a horizontal window). Both terms are modified from Field (1999). Note also that the Florida Springs Nomenclature Committee believes that flow through an exposed conduit in the aquifer is different from flow onto the Earths surface. For this reason, the Florida Springs Nomenclature Committee does not consider a karst window to be a spring. It is an exception to the definition of a spring (See spring ). karstic aquifer An aquifer containing soluble rocks with a permeability structure that includes abundant interconnected conduits dissolved from the host rock. The interconnected conduits are organized and faci litate the circulation of fluid in the downgradient direction wherein the permeability stru cture evolved as a consequence of dissolution by fluid (Modified from Huntoon, 1995). laminar flow Flow in which the head loss is proportional to the first power of velocity. Water flowing in a laminar manner will have streamlines that remain distinct and that flow direction

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FLORIDA GEOLOGICAL SURVEY 186at every point remains unchanged with time. Darcys Law strictly applies under laminar flow conditions only (Modified from Field, 1999). limestone A sedimentary rock primarily composed of the mineral calcite (CaCO3). Limestone is soluble and often develops karst features when w eathered (Modified from SDII Global rp., 2002). magnitude See Spring magnitude nonartesian A condition in which the upper surface of the zone of saturation forms a water table under atmospheric pressure. The term is synonymous with unconfined (Field, 1999). offshore spring The point of discharge of the spring is seaward of the mean low-tide level (Copeland, 2003). onshore spring The point of discharge of the spring is landward of the mean low-tide level (Copeland, 2003). overflow stream A stream valley that is down gradient of a swallow hole, swallet, or blind valley and that carries water only when the recharge capacity of the swallow hole is exceeded. In Florida, the term is sometimes used to identify an overflow, or paleo-overflow, stream valley (Modified from SDII Global Corporation, 2002). paleokarst This term describes either an ancient karst terrane or the presence of features associated with an ancient karst terrane. The term is used to describe old sinkholes and other karst features that are no longer actively forming. In west-central Florida, the term is used to refer to sinkholes that formed decades to millions of years ago a nd are no longer active (Modified from SDII Global Corporation, 2002). paleosinkhole An ancient sinkhole that is no longer active. See relict sinkhole and alluvial sinkhole (SDII Global Corporation, 2002). photolineament A natural linear feature on the land surface that has been identified from areal photographs or other images. Photolineaments ar e identified by alignments within or between lakes and wetlands, sinkholes, stream segments, so ils, and vegetation patterns. Photolineaments are also known as photolinears Note that photolinears may or may not represent geologic features, so the term is not synonymous with fracture trace. See fracture trace (Modified from SDII Global Corporation, 2002). pipe In karst terminology, it is a semi-circular condu it through which water and soil can pass. Pipes are often nearly vertical and they have steep (nearly vertical) sides (SDII Global Corporation, 2002). polje A large flat-bottom sinkhole complex formed by the coalescence of several smaller sinkholes. Poljes are flat-bottomed because of subsequent sedimentation, usually in a lake. Paynes Prairie in Alachua County is an example (Modified from SDII Global Corporation, 2002). ponor Hole in the bottom or side of a closed de pression through which water passes to or from an underground channel (Field, 1999). It is synonymous with swallow hole raveling Raveling is the process by which water transpor ts soil particles downward into cavities in the underlying strata. Because sand is typically damp and the grains are angular, in Florida they do not easily ravel without moving water.

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BULLETIN NO. 69 187 Because of their cohesiveness, clay-rich strata are more difficult to ravel than sandy soils (SDII Global Corporation, 2002). relict sinkhole A relict (or relic) sinkhole is an ancient sinkhole that is no longer active. It may be expressed as a sinkhole lake, depression in the land surface, or loose soils in the subsurface. See paleosinkhole and alluvial sinkhole (Modified from SDII Global Corporation, 2002). resurgence re-emergence of groundwater through a karst f eature, a part or all of whose waters are derived from surface inflow into ponors at higher levels (Modified from Field, 1999). river rise see resurgence (Field, 1999). rock-collapse sinkhole A collapse sinkhole formed when the limestone, or other soluble rock, cavern ceiling fails and collapses into a void (Modi fied from SDII Global Corporation, 2002). rubble In the context of karst, rubble describes the gravel-like debris that forms as limestone is weathered (Modified from SDII Global Corporation, 2002). sag depression A sag depression is often the surficial manifestation of a solution or cover subsidence sinkhole. As the underlying bedrock is dissolved away, the cover materials slowly sag, creating a depression. Owing to the shallow water table, sags often become small, circular wetlands (SDII Global Corporation, 2002). sand boil A spring in which the vent has been filled in with sand. Spring discharge continuously suspends the sand particles that cover the spring. Thus the spring has a boiling appearance (Copeland, 2003). seep 1 To move slowly through small openi ngs of a porous material (Field, 1999). 2 With regard to springs in Florida, a seep is also a noun that infe rs one or more small openings in which water discharges diffusely (oozes) from the groundwat er environment. Discharge is from intergranular pore spaces in the matrix and flow is typically laminar (Copeland, 2003). seepage The infiltration or percolation of water through rock or soil to or from the Earths surface and is usually restricted to the very slow movement of groundwater (Field, 1999). sink See sinkhole sinkhole A landform created by subsidence of soil, sedimen t, or rock as underlying strata are dissolved by groundwater. Sinkholes can form by collapse into subterranean voids created by dissolution of limestone or dolostone or by subsidence as th ese strata are slowly dissolved away (Modified from SDII Global Corporation, 2002). siphon 1 In speleology, a cave passage in which the ceiling dips below a water surface (Monroe, 1970). 2 A flooded cave passage. A gallery (conduit) in the form of a U with water moving only under pressure when the siphon is co mpletely filled (Field, 1999). 3 Site and origin of an intermittent spring; section of a flooded cave or sump flooded passage (Field, 1999). soil piping Laterally limited, vertical areas of loose soil often caused by downward vertical movement of the soil (raveling). See pipe (Modified from SDII Global Corporation, 2002).

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FLORIDA GEOLOGICAL SURVEY 188solution sinkhole Sinkhole formed by the slow subsidence of soil or sediment as the upper surface of the underlying, water-soluble sediment or rock is removed by dissolution. See cover-subsidence sinkhole (SDII Global Corporation, 2002). source aquifer The aquifer from which the water in a spring originates (Copeland, 2003). spring A point where underground water emerges onto the Earths surface (including the ocean bottom). The image of a trickle of water springing from a hillside hardly matches that of a vast cave pouring forth a river, but both are called springs. Springs may be exsurgences or resurgences, depending upon the source of their wate r. They may also be part-time exsurgences and part-time resurgences. In some usages, spring is restricted to the water that outflows; in other usages, the word can refer to the water, the outlet, or the locality of the outflow (Field, 1999). Note that the Florida Springs Nomenclature Committee believes that flow through an exposed conduit in an aquifer is different from flow onto the earths surface. For this reason, the Florida Springs Nomenclature Committee does not cons ider a karst window to be a spring. It is an exception to the definition of a spring. spring boil Variable discharge from a spring in which hy drostatic pressure is great enough to cause a turbulent discharge (Modified from Field, 1999). spring complex See s pring group. The Florida Springs Nomenclature Committee encourages the use of spring group and discourages the use of this term. spring group A collection of individual spring vents and seeps that lie within a discrete spring recharge basin (or springshed). The individual vents and seeps of onshore spring groups almost always share a common spring run, or a tributary to the run. Spring group vents and seeps are often spread over an area of several square miles. It should be emphasized th at the term spring group will be restricted to those vents and seeps that discharge a well-define d spring recharge basin. The spring vents or seeps within a springshed may be referred to as springs. As an example, the Rainbow Springs Group will include several spring vents that drain the Rainbow Springs Group basin, and discharge into the Rainbow River spring run. Note that a spring recharge basin is defined only by potentiometric data and not by chemical or other physical characteristics of the spring discharge. However, chemical and additional physical data can, and should, be used to better define individual spring vent basins within a spring grou p basin. This type of mapping was conducted for the Rainbow Springs Group in Marion County by Jones et al. (1996). All springsheds have not been mapped. Therefore, if a springshed is not mapped, then it is acceptable to use the term springs to refer to multiple vents discharging into a common spring run. spring magnitude A category based on the volume of flow from a spring per unit time. spring pool A small body of water, either artificia lly impounded or naturally occurring, that encompasses one or more spring vents. It contains spring discharge that flows into a spring run. It contains spring discharge that flows into a spring run (The Florida Springs Nomenclature Committee, 2003). spring recharge basin Those areas within groundwater and surfacew ater basins that contribute to the discharge of the spring. The position of the divi de is orthogonal to is opotential lines (Copeland, 2003). It is synonymous with springshed

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BULLETIN NO. 69 189Note that the position of the recharge basin boundary is time dependent. That is, the boundary is representative of a snapshot in time, rather than permanent. Thus, the boundaries of springsheds are dynamic and vary as a result of a changing potentiometric surface. If a spring is found to drain one springshed during times of high potentiometry, and another basin during low times, then the spring should be connected with two spring basins in the spring database (Copeland, 2003). Whenever practical, descriptive asp ects of the recharge basin should be noted in the spring database. The following are examples. The relative recharge to groundwater within the basin should be noted. Those portions of the basi n where confined and unconfined groundwater conditions exist should also be recorded. Finally, groundwater vulnerability within the springshed should be noted if possible. A potential tool to predict vulnerability is the Florida Aquifer Vulnerability Assessment (FAVA) model (Baker et al., 2002). spring run 1 A body of flowing water that originates from a karst spring (Field, 1999). 2 A stream (river, creek, etc.) whose primary (>50 percent) source of water is from a spring, springs, or spring group (The Florida Springs Nomenclatu re Committee 2003). For example, the Wakulla River, where the predominant source of water is from Wakulla Spring, is a spring run. However, farther downstream, where surface water tributaries, contribute 50 percent or greater of the flow, the Wakulla River is no longer considered a sp ring run. A detailed hydrogeologic (e.g., the collection of discharge and seepage data) study may be needed in order to identify boundaries of a spring run (The Florida Springs Nomenclature Committee, 2003). spring seep See seep spring vent See vent. springs Multiple spring vents or seeps located in proximity to each other. The usage of this term is discouraged, but for pragmatic reasons, it cannot be entirely dropped. For example, several vents may discharge into a common spring run and the collection of scientific data (e.g. water samples or disch arge measurements) cannot be obtained from individual vents located in the run. However, it may be practical to obtain a composite water sample or composite flow measurement representing several vents. Under this situation, the term springs is acceptable. However, a list of each vent or seep represented by the composite sample should be recorded by the sampler, and ultimat ely placed into the spring database (Copeland, 2003). steephead A deeply cut valley, generally short, terminati ng at its upslope end in an amphitheater, at the foot of which a stream may emerge; e.g., ocean, lake, river, or stream (Field, 1999). springshed See spring recharge basin. subaqueous spring A spring that discharges below the surface of a water body (Field, 1999). The term implies a pre-existing receiving surfacewater body and is synonymous with submerged (Poucher and Copeland, 2006). submerged See subaqueous submarine spring See offshore spring

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FLORIDA GEOLOGICAL SURVEY 190swallet See swallow hole swallow hole A place where water disappears underground in a limestone region. A swallow hole generally implies water loss in a closed depression or blind valley, whereas a swallet may refer to water loss into alluvium at a streambed, even though there is no depression (Field, 1999). tidal spring A spring whose discharge is controlled by tidal cycles. Near the coast, tidal springs may alternately discharge saline and fresh water. In land, the pattern of fresh water discharge may simply reflect tidal changes in the potentiome tric surface (SDII Global Corporation, 2002). turbulent flow The flow conditions in which inertial fo rces predominate over viscous forces and in which head loss is not linearly related to velocity It is typical of flow in surfacewater bodies and subsurface conduits in karst te rranes, provided that the conduits have a minimum diameter of approximately 2-5 mm, although some research sugg ests that 5-15 mm may be more appropriate (Modified from Field, 1999). trace See overflow stream (SDII Global Corporation, 2002). uvala Large, complex sinkholes with irregular bottoms, formed by the coalescence of several smaller closed depressions. The bottom of an uvala is characterized by multiple sinkholes and an irregular bottom (Modified from SDII Global Corporation, 2002). unconfined See nonartesian. vent An opening that concentrates groundwater dischar ge at the Earths surface, including the bottom of the ocean. The spring point of discharge is significantly larger than that of the average pore space in the surrounding rock and is often consider ed a cave or fissure. Flow from the opening is mostly turbulent (Copeland, 2003).

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Appendix B2. Interpretation of the Origins of Temporal Trends in Floridas Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends Alkalinity (Alk) The primary natural source of alkalinity is dissolution of rock materials. In limestone aq uifers, the reaction of recharging water with calcite in the limestone is: H2O + CO2 + CaCO3 Ca+2 + 2HCO3 -. Where saline water encroachment is not a problem, HCO3 is the primary source of alkalinity and the dominant anion in Florida springs. 1. The proportion of conduit flow is decreasing and diffuse flow is increasing 2. Relative contribution of water held in storage in the aquifer is increasing because of longer residence times and more opportunity to react with the host aquifer 3. A connection with the surface that allowed rapid recharge may be less efficient 4. A new, more alkaline water source has been added to the flow system 1. Conduit flow is becoming more important than diffuse flow 2. Relative contribution of water held in storage in the aquifer is decreasing because of increased rapid recharge 3. A new, more acidic water source has been introduced Ammonia/Ammonium (NH3/NH4) Ammonia/ammonium is generally not detectable in natural groundwater. Small quantities may be present near decaying organics in a chemically reducing environment. Where these analytes are reported, the sources are typically fertilizer, animal wastes, or industrial effluent. Many fertilizers contain ammonium either as ammonium nitrate, urea, or some other ammonium compound. Animal wastes (human and other) also contain ammonium and urea [(NH2)2CO]. In animal wastes and some fertilizers, much of the ammonia degasses into the atmosphere rather than entering the groundwater system. 1. Increased use of or change in formulation of fertilizers 2. New sources of waste disposal in springshed 3. Changes in waste management in springshed (new septic tanks, landfills, feedlots, etc.) 4. Increase in drainage of wetlands or natural sources of chemically reduced nitrogen 5. Decrease in the reduction/oxidation potential of the groundwater that causes an increase in nitrate reduction 1. Decreased use of or change in formulation of fertilizers 2. Reduction in the sources of waste disposal in springshed 3. Changes in waste management in springshed (septic tanks, landfills, feedlots, etc.) 4. Decrease in drainage of wetlands or natural sources of chemically reduced nitrogen 5. Increase in the reduction/oxidation potential of the groundwater that causes an increase in nitrification (ammonia/ammonium oxidation) Calcium (Ca) The primary natural source of calcium in groundwater is dissolution of rock materials. In limestone aquifers, the reaction of recharging water with calcite in the limestone is: H2O + CO2 + CaCO3 Ca+2 + 2HCO3 -. Deep groundwater flow systems in the Floridan aquifer may skim along the top of the gypsum/anhydrite-rich strata of the Middle Confining Unit of the Floridan. Here, calcium is derived from dissolution of gypsum (CaSO4.2H2O) and/or anhydrite (CaSO4). Near the coasts and where saline water encroachment is a p roblem, the saline water is a source of Ca2+as well. 1. The proportion of conduit flow is less and there is more diffuse flow 2. Relative contribution of water held in storage in the aquifer is increasing because of longer residence times and more opportunity to react with the host aquifer 3. A connection with the surface that allowed rapid recharge may be less efficient (a swallet has closed or become blocked) 4. A new, calcium-rich water source has been added to the flow system, either within the springshed or by encroachment of saline water 1. The proportion of conduit flow is increasing and there is less diffuse flow 2. Relative contribution of water held in storage in the aquifer is decreasing because of shorter residence times and less opportunity to react with the host aquifer 3. A connection with the surface that allowed rapid recharge may have developed or become more efficient (a swallet opened up) Chloride (Cl) Chloride is normally present in low concentrations in natural Florida groundwater systems. There are four important sources: (1) low concentrations in rainwater as a result of entrainment of marine aerosols, (2) mixing with seawater near Florida coasts, (3) dissolution of gypsum and/or anhydrite at the base of the upper Floridan aquifer, and (4) connate water trapped within the upper Floridan aquifer. The latter is an important issue within the St. Johns River corridor. 1. Saline water encroachment is occurring, either by lateral movement of sea water or connate water or by up-coning of water from below 2. A new source of chloride has been added to the springshed (landfill, industry, etc.) 1. Saline water intrusion is declining, probably because pumping stresses are reduced or aquifer potentials have risen 2. A source of chloride has been eliminated or reduced in the springshed (landfill, industry, etc.) Discharge or flow Spring discharge is an artifact of the recharge rate of sources water, hydraulic gradient, spring elevation relative to aquifer potentials, and spring vent geometry. 1. Increase in recharge rates (m ore rainfall and increases in elevation of the potentiometric surface) 2. Reduction of stage in the receiving water (allows for increased drainage of the aquifer) 3. Reduction in pumping stress on aquife r 1. Decrease in recharge rates (less rainfall and declines in elevation of the potentiometric surface) 2. Increase of stage in the receiving water (retards flow from the spring) 3. Increase in pumping stress on aquifer Dissolved Oxygen (DO) Dissolved oxygen content in spring water is a function of (1) oxygen content of the recharge water, (2) water temp. (the lower the temperature, the higher the oxygen solubility), (3) p resence of 1. Increase in surfacewater component of spring flow, increase in conduit flow relative to diffuse flow 2. Decrease in ambient water temperature 1. Decrease in surfacewater component of spring flow, increase in importance of diffuse flow relative to conduit flow 2. Increase in ambient water temperature BULLETIN NO. 69 191

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Appendix B2. Interpretation of the Origins of Temporal Trends in Floridas Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends biota that consume oxygen in the soils and aquifer along the flow path, (4) presence of organic and mineral matter that can be oxidized along the flow path, (5) residence time of the water in the aquifer, and (6) spring vent dynamics and rate of flow. 3. Change in sample location relative to sources of water aeration 3. Change in sample location relative to sources of water aeration Fluoride (F) The primary source of fluoride in Florida spring water is dissolution of carbonate fluorapatite [Ca5(PO4,CO3)3F], the dominant phosphate mineral in the Miocene-Pliocene Hawthorn Group. Minor fluoride concentrations may be associated with saline water encroachment. 1. Increase in flow component derived from contact with the Hawthorn Group 2. Increase in waste sources, including human and animal wastes, especially landfills and septic tanks 3. Increased industrial activity in springshed 1. Decrease in flow component derived from contact with the Hawthorn Group 2. Waste management improvement, including human and animal wastes 3. Decreased industrial activity or better chemical management in springshed Iron (Fe) Iron is a widespread component in Florida rocks, including limestone, dolostone, and siliciclastic strata of the Hawthorn Group. When included within the rock mass, the iron is often present in a reduced form as pyrite [FeS2]. Upon weathering and in a mildly reducing system, the iron remains reduced in the ferrous state (Fe2+) and it can travel with the groundwater. In a chemically oxidizing system, the iron is oxidized to Fe3+ at which time it typically precipitates as ferric hydroxide (Fe(OH)3). In springs, the moderately reducing water results in discharge of ferrous iron. Oxidation and precipitation often occur after the iron has entered the spring run. 1. Changes in water chemistry resulting in increased reduction/oxidation potential in water (dissolution of pyrite and freeing of ferric iron). This is often caused by injection of non-native water into the host aquifer. 2. Increase in sources in springshed, including waste disposal, disposal of waste iron in sinkholes, runoff from metallic sources 3. Increased use of iron-rich agricultural and horticultural plant and animal supplements 4. Changes in sample location, sample collection methods, or time of sampling that could change iron because of reduction/oxidation potentials or other physical conditions of sample. 1. Changes in water chemistry resulting in increased reduction/oxidation potential in water (precipitation of ferric hydroxide in water). 2. Decrease in sources in springshed, including waste disposal, disposal of waste iron in sinkholes, runoff from metallic sources 3. Decreased use of iron-rich agricultural and horticultural plant and animal supplements 4. Changes in sample location, sample collection methods, or time of sampling that could change iron availability and oxidation state Magnesium (Mg) In Florida, magnesium is found in dolomite [CaMg(CO3)2] and in several of the important clay minerals of the Hawthorn Group, such as palygorskite [(Mg,Al)5(Si,Al)8O20(OH)2.8H2O] and montmorillonite [(Na,Ca)0.33(Al,Mg)2Si4O10(OH)2.nH2O]. Upon weathering, these and other magnesian clay minerals release magnesium to the groundwater. Saltwater encroachment is another source of magnesium in Florida groundwater. When the magnesium coexists with fluoride derived from weathering of carbonate fluorapatite, it can be assumed that the magnesium is from Hawthorn clays. If chloride is correlated to the magnesium, saline water is a probable source. 1. Up-coning or lateral migration of saline water 2. Increased proportion of flow that is diffuse in dolomitic rocks 3. Increased use of magnesium-rich soil supplements 4. Development of a quarry up-gradient that could increase the availability of highly soluble rock dust 1. Relaxation of up-coning or lateral migration of saline water, usually as a result of reductions in pumping stresses in aquifer or increased potentials 2. Reduced proportion of flow that is diffuse in origin in dolomitic rocks 3. Decreased use of magnesium-rich soil supplements Nitrate plus Nitrite as N (NO3 + NO2 as N) There are no significant natural sources of nitrate (NO3) in groundwater in Florida. Small amounts may be derived from naturally occurring organics by nitrification, but most nitrate comes from anthropogenic activities, such as use of fertilizers, waste disposal, and industrial a pplications. In recent years, nitrate has increased in rainfall as a result of atmospheric emissions and airborne dust related to human activities. 1. Increase use of nitrate-based fertilizers (turf mangmt., row crops, golf courses and other sources have been identified as sources of nitrate increases in Fla. Springs) 2. Increase in the rate of nitrification of reduced forms of nitrogen (e.g. NO2) by lowering of the water table, addition of nutrients that promote growth of nitrification microbes in soil 3. Increased surfacewater runof f to swallets, drainage wells, etc. 1. Decrease in use of nitrate-based fertilizers, especially of rapid-release. 2. Decrease in the rate of nitrification of reduced forms of nitrogen by raising of the water table, reduction of nutrients that promote growth of nitrification microbes in soil 3. Decrease of nitrate-rich surface water runoff to storm-water facilities, swallets, drainage wells, etc. (can result from better storm water management and use of pre-treatment in storm-water infiltration basins) 4. Increase recharge and aquifer flow dynamics result in dilution and dispersion of nitrate in aquifer system Nitrogen (total) (N) Total nitrogen is an analyte that reflects ammonium/ ammonia, nitrite, nitrate, and some organic nitrogen compounds. It is sometimes used as a surrogate analyte for some or all of See above See above FLORIDA GEOLOGICAL SURVEY 192

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Appendix B2. Interpretation of the Origins of Temporal Trends in Floridas Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends these compounds. Orthophosphate as P (o-PO4) In Florida groundwater, orthophosphate is derived from several sources, including (1) weathering of phosphatic minerals in the Hawthorn Group, (2) use of fertilizers, (3) waste disposal, including solid and human wastes, and (4), to a minor extent, natural humic substances. Orthophosphate has a very limited solubility in alkaline environments, so carbonate aquifers typically have low concentrations. When springs have relatively high concentrations of orthophosphate, it is typically because the water has had a low residence time in the aquifer and there has not been sufficient time or reaction surface for buffering to occur. In other words, a conduit flow system may be indicated. 1. Increase in acidic, phosphate-rich flow supplied by surfacewater sources, especially storm-water disposal in sinkholes, swallets and siphons, to conduit flow systems 2. Increase in flow component derived from contact with the Hawthorn Group 3. Increase in phosphatic fertilizer use 4. Increase in animal waste use, including human and animal wastes 5. Increased industrial activity in springshed 1. Increase in low phosphate recharge through surfacewater sources, 2. Decrease of conduit flow component relative to the low-phosphate, diffuse flow component 3. Decrease in the flow component derived from contact with the Hawthorn Group 4. Decrease in, or better management of, phosphatic fertilizer use 5. Decrease in animal waste use or waste management improvement, including human and animal wastes 6. Decreased industrial activity or better phosphate management in springshed pH The analyte pH is a measure of the acid-base balance of water. The pH in limestone aquifers is buffered by the reaction shown under alkalinity (above), and the groundwater is typically near neutral (6.9-7.3). If pH values are low relative to the pH created by chemical equilibration with the minerals in limestone, the water has not had opportunity to equilibrate because of short residence time, insufficient reaction surface in the karst conduits, or a combination of the two. If the pH is relatively high, reactions other than equilibration with the calcite in the limestone a may be indicated. This includes reactions with the grouting materials in wells and with highly reactive, fine grained calcite. Because of the highly reactive calcite dust produced in limestone quarries, high pH groundwater may result. Some industrial wastes create relatively high pH values. 1. Reduction in the amount of more alkaline, diffuse flow relative to more acidic, conduit flow 2. Increased use of soil amendments to buffer acidic soils 3. Increase in highly soluble, carbonate dust related to the establishment of a quarry up-gradient 4. Change in sampling methods (this usually results in random noise, not a systematic change) 1. Increase in the amount of more alkaline, diffuse flow relative to more acidic, conduit flow in the water discharging from a spring 2. Decreased use of soil amendments to buffer acidic soils 3. Change in sampling methods (this usually results in random noise, not a systematic change) Potassium (K) In Florida, potassium occurs in some clay minerals, such as illite [(K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)]], and feldspars, such as orthoclase [KAlSi3O8]. These mineral sources are minor compared to sources associated with saline water intrusion and anthropogenic sources, such as fertilizer and waste disposal. 1. Increased use of potassium-rich fertilizers 2. Saline water intrusion, either as a result of increase pumping stress or reduction in aquifer potentials during droughts 1. Decreased use of potassium-rich fertilizers 2. Decrease in saline water intrusion, either as a result of reduced pumping stress or an increase in aquifer potentials Sodium (Na) The sources of sodium in Florida groundwater include saline water (seawater and connate water), animal wastes, and industrial wastes. Rainfall contains small amounts of sodium as a result of marine aerosols and dust. 1. Saline water intrusion, either as a result of increase pumping stress or reduction in aquifer potentials during droughts 2. Increased waste disposal in springshed (landfill leachate, human waste, etc.) 1. Reduction in saline water intrusion, either as a result of decreased pumping stress or increased aquifer potentials during wet periods 2. Decreased waste disposal or better waste management in springshed Specific Conductance (SC) Specific conductance is a measure of the ability of water to conduct an electrical current. The higher the concentrations of dissolved salts in the water, the higher the specific conductance. Bicarbonate, chloride, and sulfate are the constituents that contribute most to the specific conductance of an aqueous solution. 1. Increase in the proportion of diffuse flow relative to conduit flow 2. Saline water encroachment 1. Decrease in the proportion of diffuse flow relative to conduit flow 2. Reduction in saline water encroachment Strontium (Sr) Strontium is included as a trace constituent in aragonite, a calcium carbonate polymorph that commonly occurs in marine 1. Saline-water encroachment 2. Increase in the proportion of water from diffuse flow 1. Reduction in up-coning of saline-water as a result of reductions in pumping stresses or increases in aquifer potentials BULLETIN NO. 69 193

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Appendix B2. Interpretation of the Origins of Temporal Trends in Floridas Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends shells, corals, and certain algae. Therefore, when newly deposited, the carbonate sediments that become limestone and/or dolostone contain small, but important, concentrations of strontium, primarily in aragonite. As the carbonate sediments are altered to limestone or dolostone, the strontium is released to groundwater. Therefore, strontium is, in part, a good indicator of the chemical maturity of limestone. The strontium in the aragonite is derived from seawater, so seawater and saline waters in general may serve as sources for strontium in groundwater. There are few other natural sources. relative to conduit flow 2. Decrease in the proportion of water from diffuse flow relative to conduit flow Sulfate (SO4) The sources of sulfate in Florida water include (1) dissolution of gypsum or anhydrite at the top of the Middle Confining Unit of the Floridan Aquifer System, (2) oxidation of pyrite in the aquifers and confining strata, (3) seawater and connate water, and (4) minor sulfate in marine aerosols in rainfall. Organic-rich sediments, such as peat, can serve as local sources of sulfate, as well. 1. Up-coning of saline water from the bottom of the upper Floridan aquifer or saline or connate water encroachment 2. Increased proportion of diffuse flow component relative to conduit flow 3. Increases in use of gypsum as a soil amendment for alkaline soils 4. Increase waste sources in springshed 5. Increase in industrial sources in springshed 1. Reduction in up-coning of saline water from the bottom of the upper Floridan aquifer or saline or connate water intrusion 2. Decreased proportion of diffuse flow component relative to conduit flow 3. Decreases in use of gypsum as a soil amendment for alkaline soils 4. Decrease waste sources in springshed 5. Decrease in industrial sources in springshed Water Temperature (Temp) In spring systems, the water temperature generally reflects mean annual air temperature in the springshed. Low or high temperatures typically reflect conduit flow systems where seasonal variations in temperature create temperature variations that are not ameliorated by diffusion or mixing in the aquifer. 1. Climate cycles resulting in increased annual mean temperatures 2. Changes in the proportion of conduit and diffuse flow 3. Decreased influx of seasonally cool water through swallets, siphons, drainage wells, storm-water basins 1. Climate cycles resulting in decreased annual mean temperatures 2. Changes in the proportion of conduit and diffuse flow 3. Increased influx of seasonally cool water through swallets, siphons, drainage wells, storm-water basins Total Dissolved Solids (TDS) Total dissolved solids is a measure of the total mass of constituents dissolved in groundwater. 1. Major causes of increased total dissolved solids relate to saline water encroachment 2. Introduction of new water sources to aquifer through waste disposal or construction 1. Major causes of decreased total dissolved solids relate to reductions in saline water encroachment Total Kjeldahl Nitrogen (TKN) Total Kjeldahl nitrogen TKN) refers to concentrations of organic nitrogen plus ammonia/ammonium in a water sample. The organic nitrogen concentration in the water can be obtained by subtracting ammonium/ammonia concentration from TKN concentration. The presence of TKN in groundwater indicates a nearby source of organic or ammonia/ammonium nitrogen, such as a swamp or wetland or organic wastes (animal, human). The Avon Park Formation, which is part of the upper Floridan aquifer, contains peat beds that locally contribute TKN to groundwater. 1. Influx of organic materials to aquifer via swallets, siphons, injection wells, drainage wells, sinkholes in storm-water basins, etc. 2. Increase of surfacewater component in aquifer relative to groundwater with long residence time and filtration 1. Reduction in influx of organic materials to aquifer via swallets, siphons, injection wells, drainage wells, sinkholes in storm-water basins, etc. 2. Decrease of surfacewater component in aquifer relative to groundwater with long residence time and filtration Total Organic Carbon (TOC) Total organic carbon (TOC) is an analyte that is similar to TKN (above). Its sources include organic-rich sediments and animal and plant wastes. Small amounts may be disseminated in sediments, such as clays and silts of the Hawthorn Group. See above See above Total Phosphorous (TP) This includes orthophosphate as well as complex phosphates and other phosphorus, including organic phosphorus, compounds. Sources include naturally occurring org. sediments and wastes. See Total Kjeldahl nitrogen and orthophosphate See Total Kjeldahl nitrogen and orthophosphate Total Suspended Solids (TSS) This analyte constitutes the materials entrained in the water that can be recovered by filtering with an 0.45 micropore filter. 1. Introduction of surface water 2. Increase in turbulent flow in conduits (often as a result of 1. Reduction of surface water influx 2. Decrease in turbulent flow in conduits FLORIDA GEOLOGICAL SURVEY 194

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Appendix B2. Interpretation of the Origins of Temporal Trends in Floridas Groundwater Interpretation When There Is A Pattern of Analyte Origin in Groundwater Increasing Trends Decreasing Trends The analyte, therefore, reflects particulate sediment discharging from the spring, colloidal precipitates forming in the spring, and microbenthic plants and animals living in the spring. pumping) 3. Rapid introduction of aquifer or other geologic materials (sinkholes, construction, etc.) 3. Flushing of particulates (sediments) in conduits Turbidity (Turb) Turbidity is a measure of the ability of light to pass through a water sample. Turbidity is caused by particulate materials suspended in the water and some dissolved or colloidal materials that hinder light penetration. Sources of turbidity in springs include surfacewater that contains high concentrations of humic substances and/or particulate matter, chemical reactions that result on precipitation of colloidal materials, and certain forms of plankton growth. See above See above Water Level/Stage (WL) Water level, or stage, is a measure of the hydraulic potential, or elevation of an unconfined water level. In a spring, the stage is either controlled by water levels in the receiving water (the river or stream into which the spring discharges) or by the potentiometric surface of the source aquifer. Unlike rivers and streams, high stage may not reflect high discharge because of backwater effects associated with the receiving water. In fact, at highest stage, many springs (estavelles) flow backwaters from the receiving water into the aquifer. 1. Increase of aquifer potentials as a result of increased recharge 2. Increase in aquifer potentials as a result of reductions in aquifer stress (pumping) 3. Increase in stage of the receiving water (river, spring run) 1. Decrease of aquifer potentials as a result of reduced recharge 2. Decrease in aquifer potentials as a result of increases in aquifer stress (pumping) 3. Decrease in stage of the recei ving water (river, spring run) BULLETIN NO. 69 195

BULLETIN NO. 69 200 1) Combine the observations in the seasons and order them from the least to the largest 2) Let r it be the rank of Y it in the joint sample. Set RrandRRniit t n iiii 1/, i.e., R i is the rank sum of the observations in season iand Ri is the average rank for these same observations. 3) Let Nni i1 4. The Kruskal-Wallis (K-W) statistic H is then defined as )1(3 )1( 12 2 1 )1( 124 1 2 2 4 1 N n R NN N Rn NN Hi i i i i i, (A1) 4) For testing the null hypothesis at the level of significance, reject H 0 if H ha where the critical value h can be found in Table A.12 of Hollander and Wolfe (1973). 5) Large-Sample Approximation. For comparing four populations ( k=4 ), Table A.12 of Hollander and Wolfe (1973) provides critical values for14 ni. When n f o r ii 51234 ,,,,, the distribution of statistic H can be approximated by a chi-square distributi on with 3 degrees of freedom under the null hypothesis. The test thus can be performed by rejecting H 0 if H 3,; otherwise do not reject H 0. Mann-Whitney (M-W) test (o r Wilcoxon Rank Sum test) For testing seasonality of a water quality analyte, one can first perform the Kruskal-Wallis (K-W) test. If the null hypothesis { F x F x f o r ii()(),,,, 1234} is not rejected, we may conclude that there is no seasonality in the data. If the null hypothesis is rejected, we need to figure out measurements in which two seasons have di fferent distributions (different means). For comparing any two populations, the Mann-Whitney (M-W) test can be employed. For example, suppose that we want to compare measurements of a water quality analyte from two different seasons, { Y tnit i,,, 1 } and { Y tnjt j,,, 1}. The null hypothesis in this comparison is H F x F x ij 0:()() and the alternat ive hypothesis is H F x F x aij:()() or equivalently Y Y itjt where is the location shift or the difference between the two season.

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BULLETIN NO. 69 201 The Mann-Whitney (M-W) test procedur e can be performed as follows: 1) Combine the observations in the two seasons and order them from the least to the largest 2) Let r it be the rank of Y it in the joint sample. Set Wriit t ni 1, i.e., W i is the rank sum of the observations in season i. 3) One-Sided Upper-Tail Test. To test H 00: versus H a: 0 at the significance level reject H 0 if W wi where the critical value w can be found in Table A.6 of Hollander and Wolfe (1999). 4) One-Sided Lower-Tail Test. To test H 00: versus H a: 0 at the significance level reject H 0 if W nnnwiiij () 1 5) Two-Sided Test. To test H 00: versus H a: 0 at the significance level reject H 0 if W wi/2 or W nnnwiiij ()/12 6) Large-Sample Approximation. When nandnij 1010, define W W nnn nnnni iiij ijij /[()] [()] 1 112. (A2) The distribution of the statistic Wi can be approximated by the standard normal distribution N(0, 1). For the one-sided upper-tail test at th e significance level reject H 0 if Wi* z. For the one-sided lower-tail te st at the significance level reject H 0 if Wi* z. For the two-sided test, reject H 0 if |Wi* | z/2. Both M-W test and K-W test are nonpara metric tests (also ca lled distribution-free tests) that are applicable to different familie s of distributions such as normal, log-normal, and other continuous dist ributions. It should be pointed out that nonparametric tests still require independent observations. In other words, for a given season i, the observations { Y tnit i,,, 1} need to be independent for the tests to be valid. Test for Trends Mann-Kendall (M-K) Test--For each analyte and each given season, the existence of linear upward or downward trends in the data will be determined by the Mann-Kendall

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BULLETIN NO. 69 202 (M-K) test (Gilbert, 1987; Ho llander and Wolfe, 1973) or th e Seasonal-Kendall (S-K) test if seasonality is present. Regarding th e M-K test, consider observations in the ith season { Y tnit,,, 1}. The M-K test can be performed in the following steps: 1) Calculate the differences { Y Y Y Y Y Y Y Y Y Y Y Y iiiiiniiiiniinin21311322 1 ,,,,,,,,,}. 2) Let sign( Y Y isit ) be the indicator function that takes the values 1, 0, and according to the the sign of ( Y Y isit ), i.e., sign( Y Y isit ) = 1 if Y Y isit > 0, sign( Y Y isit ) = 0 if Y Y isit = 0, and sign( Y Y isit ) = -1 if Y Y isit < 0. The Mann-Kendall (M-K) statistic is KsignYYii s s t n t n it ()11 1. (A3) 3) Suppose that we want to test the null hypothesis of no trend in the data against the alternative hypothesis of an upward linear trend at the significance level We reject the null hypothesis if K k i where the critical value k can be found in Table A.21 of Hollander and Wolfe (1973). The one-sided lower-tail test and the two-sided test can be performed similarly. 3) Large sample approximation. When the sample size of the particular analyte for a given season is greater than 40 (n>40), normal approximation can be used for the trend testing. Specifically, we have (Gilbert, 1987, Chapter 16) )52)(1()52)(1( 18 1 )(1 j j q j j immm nnnKVar, (A4) where q is the number of tied groups and mj is the number of observations in the j th group. Define ZKVarKifKii ii ()/[()],/1012; Z if K ii 00 ,; and ZKVarKifKii ii ()/[()],/1012 If the H0 is true, the statistic Z i has a standard normal distribution.

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BULLETIN NO. 69 203 Sen Slope (S-S) Sens nonparametric estimator of slope is based on the Mann-Kendall approach and is intended to identify the sl ope of data regardless of seasonal influences. The first step is to calculate the number of slope estimates (N) for the time series, where N = [(n)(n-1)/2], and n = the number of observati ons in the series. Each slope estimate is determined by: i -j x x = Qij (A5) where xj and xi are the values of data collected at times i and j, and j > i. In other words, the difference in the numerator of equation A5 reflects the change in condition of a sample collected at time j as comp ared to an earlier sample colle cted at time i. If the time intervals are equal, then the denominator of equation A5 becomes a constant and equation A5 results in the differences calculated for the Mann-Kendall test. The median of the ranked series is determined as follows: Sens estimator = median slope, = Q(N + 1)/2 if N is odd, = (QN/2 + Q(N + 2)/2) if N is even. A two-sided test for confidence on the slope is determined using the table of the cumulative normal distribution. At an = 0.10, the Z1/2 is 1.64. This value from the table is compared to ] [VAR(S) Z = C0.5 /2-1 where .5)] + t 1)(2 t ( t 5) + 1)(2n [n(n 18 1 = VAR(S)p pp q=1,p (A6) The value of n is the number of samples in the time series, q is the number of ties, and tp is the number data in the pth group (the number of multiple samples in group p). For the example, n = 5 samples, q, the number of tied groups = 0, and tp, the number of ties in the pth group = 0.

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BULLETIN NO. 69 204 Time Series Models and Estimation of Trends Recall assumptions i, ii, and iii. If one of the three assumptions fails, results from the test methods may not be valid. The observations of a particular water quality analyte are collecte d in a time order and hence likely to be temporally correlated. Thus for trend analyses, one or more of the assumptions may not be valid. With this consideration in mind, the test methods described so far should only be used for initial data analysis. For a formal trend analysis, time series models should be considered. Time series models are widely applied to data analyses in many fields of economical, biological, physical and social sciences (Box and Jenkins, 1976; Brockwell and Davis, 1991; Pankratz 1991; Tsay, 2002). Let { I ti(), i 1234 ,,,} be the four indicator variables for the four s easons, respectively. For example, I tift11 (), is a spring quarter and I tift10 (), is one of the other three quarters. Let { Y tnt,,, 1} be the quarterly measurements of a water quality analyte at a given sample well. We may consider the following regression and tim e series model for the observations: YIttItti i ii i it1 4 1 4()(), (A7) where { ii,,,, 1234} are the intercepts for the four (or 12) seasons, { ii,,,, 1234} are the slopes (linear trends) for the four seasons, and { ttn ,,, 1 } are random noises that may follow an autoregressive and movi ng-average (ARMA) model. A special class of ARMA models is the autoregressive type of models that have the form: tj j p tjt 1, (A8) where p is the order of the autoregression, { j j p ,,, 1} are unknown coefficients, and the ts are assumed to be uncorrelated and with identical normal distribution N(0, 2). The models in (A7) and (A8) can be fitted simultaneously by the SAS or the Splus statistical packages. The coefficients in the models can be estimated by the maximum likelihood methods. Different hypothese s on the coefficients can be tested by model comparison. For example, we test the null hypothesis H 01234: (A9) which is equivalent to comparing model (A?) with the model

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BULLETIN NO. 69 205 YtItti i it1 4(). (A10) Similarly, we may test diffe rent hypotheses on the slopes { ii,,,, 1234}. Transformations Notice that in model (A8), the random errors ts are assumed to be uncorrelated, normally distributed, and with constant variance, which implies that the observations { Y tnt,,,1} are 1) normally distributed a nd 2) with constant variance 2. If one of the two assump tions is invalid, transforma tions should be performed on Y t to improve normality or to stabilize the variance. When { Y tnt,,,1} are positive numbers, the most popular transformation family is the Box-Cox power transformation family {Yt 33} where 0 corresponding to the logarithm transformation. In practice, an appropriate transformation for Y t is usually chosen from the class { 21510500510152 ,.,,.,,.,.,.,}. The logarithm and the square-root transformatio ns are the most popular transformations chosen in data analysis. Missing data and censored data --Missing data will cause some problems in time series analysis. Here are two ad hoc ways to impute missing data in a time series: 1) Suppose that Y t is missing, we may impute Y t by Y Y Y t tt 112 2) Another way is to impute Y t by the sample mean of the same season. For example, if the time t is a spring quarter, Y t can be imputed by the sample mean of the spring quarter observations in the series. The same way can be applied to monthly data. In water quality data analysis, censored data are usually caused by the minimum detection limit (MDL) of analytical laborat ories. A popular way is to impute censored data by MDL/2 or to simply use MDL.

BULLETIN NO. 69 209 APPENDIX F. ANALYTES APPENDIX F1. ANALYTE DESCRIPTIONS Field Analytes Field analytes represent a grouping of conve nience. Most were obtained prior to collecting samples for laboratory analyses. The analytes in this group that were used for trend analyses include discharge (or flow), dissolved oxygen, pH, specific conductance (SC), temperature (of water), and water level (msl). Discharge Discharge, or spring flow is controlled by ground-water levels in the aquifers and generally changes slowly in response to fluctuations in potentiometry. Discharge is measured in cubic feet per s econd or gallons per da y. For trend analyses, discharge is referred to as flow. Dissolved Oxygen Oxygen readily dissolves in water. It is often abbreviated to as DO. The source of oxygen can be atmo spheric or biological. Typically springs, that discharge water from a deep aquifer source, have lo w dissolved oxygen concentrations. On the other hand, in shallow ground water the dissol ved oxygen content is relatively high. This is due to a greater exposure to the atmosphe re and an increase in biological activity. pH pH measures the acidity or alkalinity of wa ter. It is defined as the negative log of the activity of the hydrogen i on in a solution. Values range between zero and 14. A low pH (below seven) represents acidic conditions, and a high pH above seven represents alkaline conditions. A pH of seven indicates the water is near neutral conditions. As raindrops form they incorporate dissolve d carbon dioxide, forming weak carbonic acid. The resulting rain has a low pH. In Florida, as rainwater passes through soil layers it incorporates organic acids and the acidity increases. When acidic water enters a limestone aq uifer, the acids react with calcium carbonate in the limestone a nd dissolution occurs. Generally, most spring water falls within a pH range of seven to eight. Regarding spring water, during heavy rain events, spring water can drop in pH as tannic acids fr om nearby surface waters are flushed into the spring system. It should be noted that sa mpled river rises tend to have a lower pH than the clear-water spring systems, due to the surface-water component of the river rise water. The pH in well water generally fa lls within the six to eight range. Specific Conductance Specific conductance (SC) is a measure of the ability of a substance, in this case ground water, to conduc t electricity at 25 C. The conductance is a function of the amount and type of ions in the water. Instead of measuring SC in the field, so me sampling agencies had their laboratory measure SC in the laboratory. For trend analyses, SC in the field (SC-field) was preferred. However, in order to generate su fficient data for time sequences A, B, and C, laboratory SC (SCL) was used if SC-field was unavailable. One sampling agency used

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FLORIDA GEOLOGICAL SURVEY 210 the term field conductance [cond(field)] for SC -field. For trend anal yses, the abbreviation SC is used. Note that it includes SC-field, and SCL. Stage The stage is the height of a water surf ace above an arbitrar ily established datum plane. For this report, stage is converted wa ter level above the Nati onal Geodetic Vertical Datum (NGVD) of 1927 (SFWMD, 2005), or approximately mean seal level (msl). It is often used in spring monitoring. Temperature (of water) Geologic material is characteristically a good insulator. Rocks and sediments tend to buffer changes in the temperature (Temp) of ground water. Thus, ground-water temperature does not vary much an d tends to reflect the average annual air temperature in the vicinity of springs or wells. In Florida, ground-water temperatures generally range from 68F to 75F (20 C to 24 C), plus or minus several tenths of a degree. It plays a role in chemical and biologi cal activity within the aquifer and can assist in determining residence time of the water in the aquifer. Water LevelIn a well, the variable water level is considered to be the distance from a measuring point located close to land surf ace downward to the ground-water surface. In data files, it is sometimes recorded as th e depth to water and abbreviated (DtoH2O). Although it is convenient to measure water levels in this manner and store them in a data base, interpreting how water le vels change over time can be somewhat confusing. For example, if potentiometric levels of an aquifer decrease over time due to a drought, potentiometric levels will drop. However, water levels as the reported in a data base will increase (the distance from land surface to the ground-water surface will increase). In order to avoid this confusion, for this report, all water level data were converted to its elevation, relative the NGVD datum of 1927, or approximately mean sea level. Thus, when levels in ground water decrease, water le vel data decrease. For this report, the converted water level data is used and is abbreviated WL(msl ); water level relative to mean sea level. Rock-Matrix Analytes Because of natural ro ck weathering, water that has ha d a long residence time in an aquifer system has a greater probability of having high concentration of rock matrix material. Thus rock-matrix analytes are those indicative of the rocks making up an aquifer. For this report, rock indicators incl ude alkalinity, calcium, magnesium, plus to a lesser extent, fluoride, iron, pH, potassium, strontium, sulfate, and specific conductance. AlkalinityIn the presence of acids, alkalinity (Alk ) results from of the dissociation of calcite (or aragonite) (CaCO3) and dolomite (CaMg (CaCO3)). The two minerals are the major mineral constituents in carbonate a quifers, such as the FAS and the Biscayne Aquifer. Upon disso lution carbonate (CO3) and bicarbonate (HCO3) are the two resulting predominant chemical species. In most natura l systems, in the pH range of 6.4 to 10.3 at 25 C, bicarbonate is the major anion. As su ch, bicarbonate is the dominant constituent of alkalinity of the water. This is the situa tion regarding alkalinity in Florida. Depending

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BULLETIN NO. 69 211 on the laboratory, either total alkalinity or bi carbonate was measured. For the purpose of trend analyses, the two analytes are considered to be very similar to each other and the term alkalinity (Alk) will repr esent either constituent. Calcium Calcium (Ca) and magnesium (Mg) are the dominant cations in the carbonate aquifers in Florida and are the major minera ls that constitute lim estone and dolostones respectively. The Floridan aquifer system is composed of calcite and dolomite. Regarding calcium, it is released upon the weathe ring carbonate rocks. It is also released upon the weathering of gypsum and anhydrite. Gypsum is occasionally found in the intermediate aquifer system and Upchurch (1992) indicated that both are common at the base of the Floridan aquifer system in the Avon Park and Oldsmar Formations. Both dissolved calcium (D-Ca) and total Ca (T -Ca) were sampled. Occasionally a sampling agency alternated between the two species. For trend analyses, whenever possible, D-Ca was used and was the species of choice. Ho wever, both species we re lumped together into a surrogate analyte (simply calcium) a nd were treated as if they were the same species. Fluoride Hem (1985) indicated that fluoride is a source of fluoride (F) is the mineral fluorapatite. This mineral is commonl y found in the Hawthorn Group of the IAS (Copeland, 1981). Both dissolved fluoride (D-F) and total fluoride (T-Fe) were sampled. For trend analyses, whenever possible, D-F was used and was the species of choice. IronThree common sources of iron (Fe) in Floridas ground water are the: (1) oxidization of the mineral pyrite, (2) oxidati on of organic compounds, and (3) dissolution of iron oxide and silicate minerals (Upchurch, 1992). It is generally more prevalent in the SAS and the IAS than the FAS. Both dissolved fluoride (D-Fe) and total fluoride (TFe) were sampled. For trend analyses, wh enever possible, D-Fe was used. Magnesium Due to chemical similarities, ma ny of the factors that govern the distribution of calcium in Fl orida aquifer systems may also be applied to magnesium. The intermediate aquifer systems Hawt horn Group contains significant sources of magnesium, including magnesium-rich clays (S trom and Upchurch, 1983). The FAS also contains abundant dolomite which is the major source of Mg in Floridas aquifer systems. Both dissolved magnesium (D-Mg) and total Mg (T-Mg) were sampled. Occasionally a sampling agency alternated betw een the two species. For trend analyses, whenever possible, D-Mg was used and wa s the species of choice. However, both species were lumped together into a surrogate analyte (magnesium) and were treated as if they were the same species. Potassium In Floridas ground water, potassium (K) is primarily derived from sea water (Upchurch, 1992). Therefore, coasta l regions, where the fresh-water/saltwater transition zone is present, t ypically contain the highest K c oncentrations. Other sources are drilling fluids in newly installed wells clay minerals, and in fertilizers. Both dissolved (D-K) and total (T-K) potassium were sampled. For trend analyses, whenever possible, D-K was used.

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FLORIDA GEOLOGICAL SURVEY 212 pH As previously stated, when acidic water en ters a limestone aquifer, the acids react with calcium carbonate in the limestone and diss olution occurs. In Florida, pH often has a direct inverse relationship with the concentr ations of Ca, Mg, and Alk. For example, during heavy rain events, spring water and sh allow ground water can drop in pH as acidic surface water recharges the aquifer systems. Specific Conductance Because it is a measure of electrical conductance at 25 C, and because it a good indicator for the dissolution of limestones and dolostones, SC is a good rock-matrix indicator. Strontium Strontium (Sr) is relatively uncomm on in Floridas aquifer systems. However, it occasionally substitutes for calcium (Upchurch, __) in the in the CaCO3 matrix of carbonate aquifers. It is more prev alent in the older, deeper, and more saline portion of the FAS. The dissolved (D-Sr) a nd the total (T-Sr) species were sampled. Whenever possible, the dissolved form was used for trend analyses. Sulfate Sulfate (SO4) is commonly found in aquifer wate rs in Florida and has several sources. The two most common sources are fr om seawater and the dissolution of gypsum and anhydrite (naturally occurring rock types w ithin Florida's aquifer systems). Sulfate is often used as a soil amendment to acidify soil s, and thus is associated with agricultural activities. Finally, disposal and industrial waste activities release sulfate to ground water. Salt-Water or Saline Analytes Saltwater analytes are those associated with salts with either connate or seawater. Connate waters are those waters trapped w ithin the sediments at the time of their deposition. Since the original sediments were deposited in a marine environment, the pore spaces contain very old sa lt water. Saltwater analytes are obviously also found in the seawater located along Floridas coasts. The major difference is the age of water. High concentrations of saltwater analytes are often an indi cation of horizontal saltwater intrusion. However, it can also be an indi cation of intrusion of highly mineralized water from the deeper portion of the Floridas fresh water lens. The intrusion can be caused by the depletion of the less dense freshwater lens during very dry period (e.g. a drought), or by the upconing of connate water during periods of heavy ground-water withdrawals. It should be noted that the pumping of gr ound water increased during dry periods and exacerbated the intrusion process. For this report, saline analytes include calcium, chloride, potassium, sodium, specific conductance, sulfate, total dissolved solids (TDS). Calcium In addition to it predominance as a rock-matrix indicator, calcium can also be considered an indicator of saltwater intrusi on. As previously stated, calcium can be released into Floridas gr ound water from the weathering of gypsum and anhydrite found at the base of the Floridan aquifer system. If calcium concentrations are found to be

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BULLETIN NO. 69 213 increasing, in conjunction with sulfate, it can be an indica tion that the ol der and deeper water from the base of the fresh water lens is finding its way into the shallower portions of Floridas ground-water systems. If this occurs, there is the potential that increases in the concentration of othe r saltwater indicators will follow. Chloride Chloride (Cl) is the most abundant constituent in seawater. Ground water and spring water that are tidally influenced may have high chloride concentrations. Other sources for Cl in Florida are from rainfall via marine aerosols from the ocean, and as a by-product of waste. Chloride is chemically conservative and reacts very little with ground water. Potassium As stated previously, K is primarily de rived from sea water. However, it can be introduced into ground wa ter via fertilizers. Another source is from drilling fluids in newly installed wells, and from clay minerals. Sodium In Florida, sodium (Na) in ground water has several sources. The major source is the mixing of seawater with fresh water. Two other, but relatively minor sources are marine aerosols and the weathering of sodium-b earing minerals like feldspars and clays. Thus, to a very minor degree, sodium can also be considered a rock analyte. However, for this report is considered a saline analyt e. Both dissolved sodium (D-Na) and total sodium (T-Na) were sampled. The species D-Na was preferred for trend analyses. Specific Conductance Because it is a measure of electrical conductance, and because it highly mineralized water has a concentrati on of SC, it is a good indicator of saline conditions. Sulfate Because of its source (gypsum and anhydrite), SO4 is considered to be a rock indicator. However, as prev iously stated, sulfate can be released into Floridas ground water from the weathering of gypsum and anhy drite found at the base of the Floridan aquifer system, and because seawater is also an important source of sulfate in coastal areas, sulfate is an excelle nt saltwater indicator. Total Dissolved Solids As stated previously, TDS is primarily derived from the dissolution of carbonate rocks in Floridas aquifers. It is al so originates from saline and connate marine water. Nutrient Analytes These analytes represent compounds or elem ents that are essential for the growth of living organisms. They occur naturally. However, if found in high concentrations, it can cause the over-enriching of a body of su rface water (eutrophication), leading to an overgrowth of plant life (including algae) and possibly a loss of dissolved oxygen. For this report, nutrient analytes include phosphate, phosphorous, a se ries of nitrogen related

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FLORIDA GEOLOGICAL SURVEY 214 species, and to a lesser extent, Mg, Ca, K, and sulfur in the form of sulfate. The nitrogen related species include nitrogen, ammonia, total kjeldahl nitrogen, nitr ate, and nitrite. Calcium Since calcium is an essential nutrient and is a major ingredient in fertilizers, it is included in the nutrient analyte category. Magnesium As with calcium, magnesium is an essential nutrient and is a major ingredient in fertilizers. Thus, it is included in the nutrient analyte category. Nitrogen For this report, the monitored nitrogen species is total ni trogen. The amount of ammonia, nitrate, nitrite, and organic ni trogen, when summed, gives the total nitrogen (T-N) content of ground water. For ground wate r, the major sources are fertilizers and animal excrement. Ammonia and ammonium Taken from Upchurch (1992), nitrate is one member of a sequence of related nitrogen com pounds that includes nitrogen gas (N2), nitrite or nitrogen dioxide gas (NO2) and other oxides, ammonia and ammonium (NH3, NH4), a number of other inorganic and organic compounds. The gaseous phases exist in the atmosphere and in soil atmospheres, but are not of importance in the saturated zones of aquifers. Ammonia gas also escapes into th e atmosphere. Thus, a mmonia is present in ground water in the form of ammonium (NH4) because of the prevalent pH conditions and reduction-oxidation potentials. A source of the nitrogen can be from fertilizers and animal excrement. Nitrate and Nitrite Nitrate (NO3) and nitrite (NO2) are both found in Floridas ground and spring water. In terms of abundance, in oxidizing environments, nitrate dominates significantly over nitrite. For th is reason, nitrate is not often measure by itself. Rather, it is measured as part of a nitrate species. The monitored species of nitrate are dissolved nitrate plus nitrite as N (DNO3 + NO2), dissolved nitrate as N (DNO3), total nitrate plus nitrite as N (T-NO3+NO2), and total nitrate as N (T-NO3). The concentrations of all of these analytes are considered to be measures of nitrate. Nitrate contamination recently has become a problem in Florida's ground and spring water. Nitrate often originates from fertilizers, septic tanks and animal waste that enter the aquifer in the spring recharge area. Nitrate, being a nutrien t, encourages algal and aquatic plant growth in spring water, wh ich may lead to eutrophication of the spring run or associated water body. N itrite, which is much less of a problem, can originate from sewage and other orga nic waste products. Organic Carbon Natural and non-naturally occurri ng organic carbon are present in varying concentrations in spring water in Florida. The primary source of naturally occurring organic carbon is humic substanc es (decaying plant material). Synthetic organic carbon represents a minor component The species sampled was total organic carbon (TOC).

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BULLETIN NO. 69 215 PhosphatePhosphate as monitored is orthophosphate (PO4) as P. It is an essential nutrient and occurs in ground water in Florid a. Unfortunately, an excess of phosphate can cause run-away plant growth and the eutr ophication of surface waters. The mineral fluorapatite found in the Hawthorn Group in the IAS is possibly the most important source of phosphate in ground water in Florida. However, other sources include organic and inorganic fertilizers, animal waste, human waste effluent and industrial waste. Both dissolved (D-PO4) and total (T-PO4) orthophosphate were sa mpled. The species D-PO4 was preferred for trend analyses. Phosphorous Total phosphorous (T-P) is the sp ecies of phosphorous monitored in spring water by the water management districts of Florida. It includes the total of several oxidation states that range from P3to P5-. Phosphorous can originate from the mineral fluorapatite. However, it is a component of sewage. It presence in can cause the eutrophication of surface water. PotassiumSince K is a major ingredient in fertil izers, it is included in the nutrient analyte category. Sulfate Since SO4 is an ingredient in fertilizers, it is included in the nutrient analyte category. Total Kjeldahl Nitrogen Total kjeldahl nitrogen (TKN) is a measure of the sum of the ammonia nitrogen and organi c nitrogen in the ground water sample. The ammonia nitrogen, mainly occurring as ammonium (NH4), occurs in trace amounts in ground water. Organic nitrogen originates from bi ological sources including sewage and other waste. It is also found natu rally in the Avon Park Formati on toward the base of the FAS (Upchurch, 2000). Other Analytes Analytes in the Other category do not fit in the other four. They represent a miscellaneous group. For trend analyses, the analytes included in this group are organic carbon, suspended solids, and turbidity. Suspended Solids These refers to the total amount of solid material suspended in the water column. As opposed to turbidity, total suspended so lids (TSS) do not take into account the light scattering ability of the wate r. TSS are filtered out of a water sample. TurbidityTurbidity is a measure of the colloid al suspension of tiny particles and precipitates in spring water. High turbidity wa ter impedes the penetration of light and can be harmful to aquatic life. Most Florida springs discharge water low in turbidity.

FLORIDA GEOLOGICAL SURVEY 220 APPENDIX H. DATA FROM SPRINGS AND WELLS All data related to this st udy are available online at: http://publicfiles.dep.state.fl.us/FGS/FGS_Publications /B/B69Appendices/APPENDIX_H _(Spring_and_Well_Data)/ The entire data set is located within the fold er entitled Data. The actual raw data from the WMDs and the DEP TV Network that was us ed for seasonality tests and the trend analysis are divided into three regions of the state, Northwest, Central, and South Florida. Within these regions Northwest contains th e spring and well data from within the Northwest and Central WMD, Central contains the spring and well data from St. Johns and Southwest WMDs, and South contains th e spring and well data from South Florida WMD. Figure H1. Flow diagram for water quality data in the online directory. Diagram explaining raw data from WMDs and DEP TV Network. SJRWMD SWFWMD Northwest Florida NWFWMD SRWMD SFWMD Central Florida South Florida Data Individual Spring and Well Data ( 1991-2003)